# Plushcap Board-prep trend context

Review quarter: Q3 2026, 2026-07-01 through 2026-09-30.
Previous quarter: 2026-04-01 through 2026-06-30.
Latest three completed months: 2026-08-01 through 2026-10-31.

## Usage and constructive Board framing

Lead with supported accomplishments and relevant market alignment. Present uncovered, growing trends as potential next-quarter investments. Prioritize opportunities that fit the company's product and audience. Keep material qualifications concise and attached to the claims they affect.

Supply your company, audience, reviewed quarter, explicit planning-quarter dates, campaigns, results, and product priorities. Ask for slide bullets, speaker notes, and a sourced evidence appendix. If the requested quarter is outside these dates, identify the missing evidence. If your assistant cannot fetch this URL, paste the complete file into the conversation. No MCP setup is required.

## Optional: get more detailed data with Plushcap MCP

This file is a compact public summary. For significantly more detailed, company-specific research, connect Plushcap's read-only MCP server to your AI assistant. It can retrieve company details, searchable blog posts, video publishing activity and YouTube audience metrics, Hacker News submissions, detailed trend histories, and competitive comparisons. X and LinkedIn data are also available where your account has access. Data availability, history, and quotas follow your existing Plushcap access tier and tracked-company coverage; installation does not unlock restricted data or fill gaps in historical coverage.

### ChatGPT: install the Plushcap plugin

1. [Install Plushcap in ChatGPT](https://chatgpt.com/plugins/plugin_asdk_app_6ac67fc9925481918c4ec65a0f42c134). This direct installation link opens the Plushcap plugin page; select the plus button to install it.
2. Connect your Plushcap account when prompted: sign in and approve the connection so ChatGPT can query the data available to your account.
3. Start a new chat and ask ChatGPT to use Plushcap to enhance your Board narrative. If a connection prompt appears on first use, complete it before requesting company data.

### Antigravity: connect the Plushcap MCP server

1. Add the following configuration to Antigravity's global `~/.gemini/config/mcp_config.json`. If you already have an `mcpServers` object, merge the `plushcap` entry into it rather than replacing your other servers.

```json
{
  "mcpServers": {
    "plushcap": {
      "serverUrl": "https://mcp.plushcap.com/mcp"
    }
  }
}
```

2. In the Antigravity app, open Settings > Customizations, refresh the installed MCP servers, and choose Authenticate for Plushcap. Complete the browser sign-in and authorize access to your Plushcap account. If Antigravity requests an authorization-code handoff, complete it in its authentication panel, not in the chat.
3. Ask Antigravity to use Plushcap with the research prompt below. In Antigravity CLI, use `/mcp` to inspect the connection and follow its authentication prompts.

See the [Plushcap Antigravity guide](https://www.plushcap.com/docs/mcp/antigravity-cli.md) and [Google's MCP instructions](https://antigravity.google/docs/mcp).

### Claude: connect on the web or Desktop

1. Open Customize > Connectors in Claude, select Add custom connector, and name it Plushcap. Use this remote MCP server URL: `https://mcp.plushcap.com/mcp`.
2. Follow the connection prompts, using OAuth sign-in and automatic client registration if asked. Sign in to your Plushcap account and authorize access. In a managed workspace, an administrator may need to add or enable the connector first.
3. Open the chat's + menu, choose Connectors, and enable Plushcap. Ask Claude to use it with the research prompt below.

Setup guides: [Claude Web](https://www.plushcap.com/docs/mcp/claude-web.md) and [Claude Desktop](https://www.plushcap.com/docs/mcp/claude-desktop.md). See also [Anthropic's custom-connector instructions](https://support.claude.com/en/articles/11175166-get-started-with-custom-connectors-using-remote-mcp).

### Claude Code

Add the remote HTTP server from your terminal:

```bash
claude mcp add --transport http plushcap https://mcp.plushcap.com/mcp
```

Then run `/mcp` inside Claude Code and authenticate Plushcap through the browser. Sign in to Plushcap and approve the connection.

See the [Plushcap Claude Code guide](https://www.plushcap.com/docs/mcp/claude-code.md) and [Claude Code's MCP instructions](https://code.claude.com/docs/en/mcp).

### Research prompt for any connected assistant

```text
Use Plushcap to find our company: [company name], [website URL].
Retrieve available company-specific evidence for [review quarter and dates],
including publishing activity, YouTube audience metrics, relevant social
activity, and Hacker News submissions. Add detailed trend history and
competitive context where useful to our product and audience.
Use that evidence to strengthen our Board narrative: supported wins,
alignment with developer and AI trends, and next-quarter opportunities.
Cite source links and dates. Distinguish the periods actually covered from
our requested quarter, and identify missing or inaccessible data.
Do not infer pipeline or revenue impact without our internal outcome data.
```

For additional AI assistants, follow the [Plushcap MCP setup guide](https://www.plushcap.com/docs/mcp.md). ChatGPT's general installation steps are documented in the [official plugin guide](https://learn.chatgpt.com/docs/plugins). You can continue using the public context below without installing or connecting anything.

## Scope and calculation method

Public sources: Blog, X (all account types), YouTube. LinkedIn is excluded under existing access rules. Active non-product topics only. Hacker News is available on company pages, not in the trend index. Restricted reports and private company scores are excluded.

Quarterly totals sum monthly normalized mention counts, using the stored normalization caps and quarantine decisions. Growth is calculated from period totals, never from averaged monthly percentages. Each platform is reported separately; high-frequency X activity is not an independent combined-volume signal. Distinct companies are deduplicated across each complete quarter by the batch reader, never summed from monthly company counts. A calculated zero differs from a missing month. Missing or zero baselines do not produce infinite growth. No projections.

Calculation timestamps below describe the source snapshots. A newly rendered file does not imply refreshed or complete source data. Pending refreshes are labeled; uncalculated months remain missing.

Publishing about a growing trend establishes alignment, not campaign success. Absence from a declining topic does not prove deliberate focus. Continued growth is an opportunity hypothesis, not a guaranteed outcome. Revenue and pipeline claims require company-supplied outcome data.

## Blog: established trends and quarterly comparisons

Calculation timestamps (UTC): 2026-11-03T15:19:43.925368+00:00 through 2026-11-03T15:39:03.910122+00:00. These are snapshot calculation times, not proof of complete ingestion.

Bounded selection: up to 8 largest complete review-quarter totals, 4 largest absolute quarterly gains, incomplete coverage examples, and sustained risers per source. This is not an exhaustive trend list.

### [MCP](https://www.plushcap.com/trends/monthly/mcp?source=blog)

Model Context Protocol for AI agents

Monthly normalized mentions: 2026-07-01: 8,672; 2026-08-01: 8,097; 2026-09-01: 10,058.
Review total: 26827; previous-quarter total: 24930; quarter-over-quarter: +7.6%.
Distinct publishing companies across review quarter: 314.

### [LLM](https://www.plushcap.com/trends/monthly/llm?source=blog)

Large Language Models and related technologies

Monthly normalized mentions: 2026-07-01: 7,099; 2026-08-01: 5,066; 2026-09-01: 5,507.
Review total: 17672; previous-quarter total: 22837; quarter-over-quarter: -22.6%.
Distinct publishing companies across review quarter: 353.

### [AI Agents](https://www.plushcap.com/trends/monthly/ai-agents?source=blog)

AI-powered autonomous agents and agentic frameworks

Monthly normalized mentions: 2026-07-01: 6,646; 2026-08-01: 5,385; 2026-09-01: 5,031.
Review total: 17062; previous-quarter total: 19501; quarter-over-quarter: -12.5%.
Distinct publishing companies across review quarter: 359.

### [Real-time](https://www.plushcap.com/trends/monthly/real-time?source=blog)

Real-time data processing and streaming

Monthly normalized mentions: 2026-07-01: 6,113; 2026-08-01: 4,094; 2026-09-01: 4,226.
Review total: 14433; previous-quarter total: 19270; quarter-over-quarter: -25.1%.
Distinct publishing companies across review quarter: 349.

### [Observability](https://www.plushcap.com/trends/monthly/observability?source=blog)

Observability and distributed tracing

Monthly normalized mentions: 2026-07-01: 4,057; 2026-08-01: 3,088; 2026-09-01: 2,682.
Review total: 9827; previous-quarter total: 12690; quarter-over-quarter: -22.6%.
Distinct publishing companies across review quarter: 283.

### [Voice AI](https://www.plushcap.com/trends/monthly/voice-ai?source=blog)

Speech and voice AI agents.

Monthly normalized mentions: 2026-07-01: 3,657; 2026-08-01: 2,561; 2026-09-01: 1,730.
Review total: 7948; previous-quarter total: 10596; quarter-over-quarter: -25.0%.
Distinct publishing companies across review quarter: 94.

### [Kubernetes](https://www.plushcap.com/trends/monthly/kubernetes?source=blog)

Kubernetes container orchestration

Monthly normalized mentions: 2026-07-01: 1,968; 2026-08-01: 2,765; 2026-09-01: 1,849.
Review total: 6582; previous-quarter total: 5986; quarter-over-quarter: +10.0%.
Distinct publishing companies across review quarter: 187.

### [Vector Search](https://www.plushcap.com/trends/monthly/vector-search?source=blog)

Vector databases and similarity search

Monthly normalized mentions: 2026-07-01: 2,273; 2026-08-01: 2,354; 2026-09-01: 1,625.
Review total: 6252; previous-quarter total: 6834; quarter-over-quarter: -8.5%.
Distinct publishing companies across review quarter: 222.

### [AI Model Fine-tuning](https://www.plushcap.com/trends/monthly/ai-model-fine-tuning?source=blog)

Post-training AI models to achieve further performance.

Monthly normalized mentions: 2026-07-01: 945; 2026-08-01: 499; 2026-09-01: 615.
Review total: 2059; previous-quarter total: 1727; quarter-over-quarter: +19.2%.
Distinct publishing companies across review quarter: 125.

### [Local AI](https://www.plushcap.com/trends/monthly/local-ai?source=blog)

Self-hosted, local models that can be run on device.

Monthly normalized mentions: 2026-07-01: 144; 2026-08-01: 104; 2026-09-01: 161.
Review total: 409; previous-quarter total: 195; quarter-over-quarter: +109.7%.
Distinct publishing companies across review quarter: 51.

### [WebMCP](https://www.plushcap.com/trends/monthly/webmcp?source=blog)

Web application functionality exposed as tools that agents can use.

Monthly normalized mentions: 2026-07-01: 47; 2026-08-01: 77; 2026-09-01: 90.
Review total: 214; previous-quarter total: 21; quarter-over-quarter: +919.0%.
Distinct publishing companies across review quarter: 15.

### [Agent sandbox](https://www.plushcap.com/trends/monthly/agent-sandbox?source=blog)

Sandboxed code execution environments and safety for AI agents.

Monthly normalized mentions: 2026-07-01: 47; 2026-08-01: 65; 2026-09-01: 74.
Review total: 186; previous-quarter total: 75; quarter-over-quarter: +148.0%.
Distinct publishing companies across review quarter: 23.

### [AI Coding Agent Pricing](https://www.plushcap.com/trends/monthly/ai-coding-tool-and-agent-pricing?source=blog)

Trends around pricing and packaging of AI coding tools and agents.

Monthly normalized mentions: 2026-07-01: 5; 2026-08-01: 6; 2026-09-01: 11.
Review total: 22; previous-quarter total: 51; quarter-over-quarter: -56.9%.
Distinct publishing companies across review quarter: 11.

### [Serverless](https://www.plushcap.com/trends/monthly/serverless?source=blog)

Serverless computing and FaaS

Monthly normalized mentions: 2026-07-01: 780; 2026-08-01: 862; 2026-09-01: 1,109.
Review total: 2751; previous-quarter total: 3119; quarter-over-quarter: -11.8%.
Distinct publishing companies across review quarter: 186.

### Growing trends and sustained momentum

Largest absolute quarterly gains: MCP, Kubernetes, AI Model Fine-tuning, Local AI. Absolute figures and baselines appear above.
Sustained review-quarter risers: WebMCP: mentions increased for three consecutive months; Agent sandbox: mentions increased for three consecutive months.

### Recent momentum: 2026-08-01 through 2026-10-31

This rolling three-completed-month window overlaps the review quarter; it is not a new calendar-quarter result.

- MCP: 2026-08-01: 8,097; 2026-09-01: 10,058; 2026-10-01: 10,423; window total: 28578.
- LLM: 2026-08-01: 5,066; 2026-09-01: 5,507; 2026-10-01: 6,012; window total: 16585.
- AI Agents: 2026-08-01: 5,385; 2026-09-01: 5,031; 2026-10-01: 6,382; window total: 16798.
- Real-time: 2026-08-01: 4,094; 2026-09-01: 4,226; 2026-10-01: 3,480; window total: 11800.
- Observability: 2026-08-01: 3,088; 2026-09-01: 2,682; 2026-10-01: 2,939; window total: 8709.
- Voice AI: 2026-08-01: 2,561; 2026-09-01: 1,730; 2026-10-01: 2,080; window total: 6371.
- Kubernetes: 2026-08-01: 2,765; 2026-09-01: 1,849; 2026-10-01: 1,427; window total: 6041.
- Vector Search: 2026-08-01: 2,354; 2026-09-01: 1,625; 2026-10-01: 1,734; window total: 5713.
- AI Model Fine-tuning: 2026-08-01: 499; 2026-09-01: 615; 2026-10-01: 730; window total: 1844.
- Local AI: 2026-08-01: 104; 2026-09-01: 161; 2026-10-01: 98; window total: 363.
- WebMCP: 2026-08-01: 77; 2026-09-01: 90; 2026-10-01: 42; window total: 209.
- Agent sandbox: 2026-08-01: 65; 2026-09-01: 74; 2026-10-01: 24; window total: 163.
- AI Coding Agent Pricing: 2026-08-01: 6; 2026-09-01: 11; 2026-10-01: 12; window total: 29.
- Serverless: 2026-08-01: 862; 2026-09-01: 1,109; 2026-10-01: 1,266; window total: 3237.

Sustained recent risers: AI Coding Agent Pricing: mentions increased for three consecutive months; Serverless: mentions increased for three consecutive months.

## X: established trends and quarterly comparisons

Calculation timestamps (UTC): 2026-10-30T10:40:38.043521+00:00 through 2026-11-03T13:16:38.791300+00:00. These are snapshot calculation times, not proof of complete ingestion.

Bounded selection: up to 8 largest complete review-quarter totals, 4 largest absolute quarterly gains, incomplete coverage examples, and sustained risers per source. This is not an exhaustive trend list.

### [AI Agents](https://www.plushcap.com/trends/monthly/ai-agents?source=x)

AI-powered autonomous agents and agentic frameworks

Monthly normalized mentions: 2026-07-01: 284; 2026-08-01: 361; 2026-09-01: 509.
Review total: 1154; previous-quarter total: 945; quarter-over-quarter: +22.1%.
Distinct publishing companies across review quarter: 197.

### [MCP](https://www.plushcap.com/trends/monthly/mcp?source=x)

Model Context Protocol for AI agents

Monthly normalized mentions: 2026-07-01: 204; 2026-08-01: 283; 2026-09-01: 317.
Review total: 804; previous-quarter total: 647; quarter-over-quarter: +24.3%.
Distinct publishing companies across review quarter: 157.

### [Real-time](https://www.plushcap.com/trends/monthly/real-time?source=x)

Real-time data processing and streaming

Monthly normalized mentions: 2026-07-01: 150; 2026-08-01: 200; 2026-09-01: 271.
Review total: 621; previous-quarter total: 621; quarter-over-quarter: +0.0%.
Distinct publishing companies across review quarter: 138.

### [LLM](https://www.plushcap.com/trends/monthly/llm?source=x)

Large Language Models and related technologies

Monthly normalized mentions: 2026-07-01: 137; 2026-08-01: 149; 2026-09-01: 161.
Review total: 447; previous-quarter total: 415; quarter-over-quarter: +7.7%.
Distinct publishing companies across review quarter: 136.

### [Observability](https://www.plushcap.com/trends/monthly/observability?source=x)

Observability and distributed tracing

Monthly normalized mentions: 2026-07-01: 106; 2026-08-01: 114; 2026-09-01: 127.
Review total: 347; previous-quarter total: 337; quarter-over-quarter: +3.0%.
Distinct publishing companies across review quarter: 69.

### [Vector Search](https://www.plushcap.com/trends/monthly/vector-search?source=x)

Vector databases and similarity search

Monthly normalized mentions: 2026-07-01: 103; 2026-08-01: 104; 2026-09-01: 120.
Review total: 327; previous-quarter total: 271; quarter-over-quarter: +20.7%.
Distinct publishing companies across review quarter: 59.

### [Voice AI](https://www.plushcap.com/trends/monthly/voice-ai?source=x)

Speech and voice AI agents.

Monthly normalized mentions: 2026-07-01: 60; 2026-08-01: 58; 2026-09-01: 155.
Review total: 273; previous-quarter total: 222; quarter-over-quarter: +23.0%.
Distinct publishing companies across review quarter: 43.

### [AI Coding Assistant](https://www.plushcap.com/trends/monthly/ai-coding-assistant?source=x)

AI-powered coding assistants and pair programmers

Monthly normalized mentions: 2026-07-01: 72; 2026-08-01: 66; 2026-09-01: 89.
Review total: 227; previous-quarter total: 217; quarter-over-quarter: +4.6%.
Distinct publishing companies across review quarter: 68.

### [Platform Engineering](https://www.plushcap.com/trends/monthly/platform-engineering?source=x)

Internal developer platforms and platform engineering

Monthly normalized mentions: 2026-07-01: 12; 2026-08-01: 15; 2026-09-01: 16.
Review total: 43; previous-quarter total: 28; quarter-over-quarter: +53.6%.
Distinct publishing companies across review quarter: 24.

### [Serverless](https://www.plushcap.com/trends/monthly/serverless?source=x)

Serverless computing and FaaS

Monthly normalized mentions: 2026-07-01: 28; 2026-08-01: 42; 2026-09-01: 61.
Review total: 131; previous-quarter total: 103; quarter-over-quarter: +27.2%.
Distinct publishing companies across review quarter: 27.

### Growing trends and sustained momentum

Largest absolute quarterly gains: AI Agents, MCP, Vector Search, Voice AI. Absolute figures and baselines appear above.
Sustained review-quarter risers: Vector Search: mentions increased for three consecutive months; Platform Engineering: mentions increased for three consecutive months.

### Recent momentum: 2026-08-01 through 2026-10-31

This rolling three-completed-month window overlaps the review quarter; it is not a new calendar-quarter result.

- AI Agents: 2026-08-01: 361; 2026-09-01: 509; 2026-10-01: 581; window total: 1451.
- MCP: 2026-08-01: 283; 2026-09-01: 317; 2026-10-01: 370; window total: 970.
- Real-time: 2026-08-01: 200; 2026-09-01: 271; 2026-10-01: 256; window total: 727.
- LLM: 2026-08-01: 149; 2026-09-01: 161; 2026-10-01: 165; window total: 475.
- Observability: 2026-08-01: 114; 2026-09-01: 127; 2026-10-01: 132; window total: 373.
- Vector Search: 2026-08-01: 104; 2026-09-01: 120; 2026-10-01: 113; window total: 337.
- Voice AI: 2026-08-01: 58; 2026-09-01: 155; 2026-10-01: 201; window total: 414.
- AI Coding Assistant: 2026-08-01: 66; 2026-09-01: 89; 2026-10-01: 106; window total: 261.
- Platform Engineering: 2026-08-01: 15; 2026-09-01: 16; 2026-10-01: 12; window total: 43.
- Serverless: 2026-08-01: 42; 2026-09-01: 61; 2026-10-01: 78; window total: 181.

Sustained recent risers: Serverless: mentions increased for three consecutive months; AI Agents: mentions increased for three consecutive months; MCP: mentions increased for three consecutive months; Observability: mentions increased for three consecutive months.

## YouTube: established trends and quarterly comparisons

Calculation timestamps (UTC): 2026-11-03T14:19:36.075152+00:00 through 2026-11-03T22:17:01.998221+00:00. These are snapshot calculation times, not proof of complete ingestion.

Bounded selection: up to 8 largest complete review-quarter totals, 4 largest absolute quarterly gains, incomplete coverage examples, and sustained risers per source. This is not an exhaustive trend list.

### [AI Agents](https://www.plushcap.com/trends/monthly/ai-agents?source=youtube)

AI-powered autonomous agents and agentic frameworks

Monthly normalized mentions: 2026-07-01: 953; 2026-08-01: 720; 2026-09-01: 873.
Review total: 2546; previous-quarter total: 2853; quarter-over-quarter: -10.8%.
Distinct publishing companies across review quarter: 210.

### [MCP](https://www.plushcap.com/trends/monthly/mcp?source=youtube)

Model Context Protocol for AI agents

Monthly normalized mentions: 2026-07-01: 771; 2026-08-01: 667; 2026-09-01: 813.
Review total: 2251; previous-quarter total: 2043; quarter-over-quarter: +10.2%.
Distinct publishing companies across review quarter: 145.

### [Observability](https://www.plushcap.com/trends/monthly/observability?source=youtube)

Observability and distributed tracing

Monthly normalized mentions: 2026-07-01: 555; 2026-08-01: 507; 2026-09-01: 604.
Review total: 1666; previous-quarter total: 1540; quarter-over-quarter: +8.2%.
Distinct publishing companies across review quarter: 86.

### [LLM](https://www.plushcap.com/trends/monthly/llm?source=youtube)

Large Language Models and related technologies

Monthly normalized mentions: 2026-07-01: 457; 2026-08-01: 422; 2026-09-01: 542.
Review total: 1421; previous-quarter total: 1363; quarter-over-quarter: +4.3%.
Distinct publishing companies across review quarter: 134.

### [Real-time](https://www.plushcap.com/trends/monthly/real-time?source=youtube)

Real-time data processing and streaming

Monthly normalized mentions: 2026-07-01: 255; 2026-08-01: 308; 2026-09-01: 297.
Review total: 860; previous-quarter total: 1194; quarter-over-quarter: -28.0%.
Distinct publishing companies across review quarter: 131.

### [AI Coding Assistant](https://www.plushcap.com/trends/monthly/ai-coding-assistant?source=youtube)

AI-powered coding assistants and pair programmers

Monthly normalized mentions: 2026-07-01: 302; 2026-08-01: 263; 2026-09-01: 262.
Review total: 827; previous-quarter total: 818; quarter-over-quarter: +1.1%.
Distinct publishing companies across review quarter: 93.

### [Voice AI](https://www.plushcap.com/trends/monthly/voice-ai?source=youtube)

Speech and voice AI agents.

Monthly normalized mentions: 2026-07-01: 264; 2026-08-01: 166; 2026-09-01: 336.
Review total: 766; previous-quarter total: 605; quarter-over-quarter: +26.6%.
Distinct publishing companies across review quarter: 50.

### [Kubernetes](https://www.plushcap.com/trends/monthly/kubernetes?source=youtube)

Kubernetes container orchestration

Monthly normalized mentions: 2026-07-01: 155; 2026-08-01: 139; 2026-09-01: 175.
Review total: 469; previous-quarter total: 469; quarter-over-quarter: +0.0%.
Distinct publishing companies across review quarter: 48.

### [AI Model Fine-tuning](https://www.plushcap.com/trends/monthly/ai-model-fine-tuning?source=youtube)

Post-training AI models to achieve further performance.

Monthly normalized mentions: 2026-07-01: 37; 2026-08-01: 114; 2026-09-01: 37.
Review total: 188; previous-quarter total: 66; quarter-over-quarter: +184.8%.
Distinct publishing companies across review quarter: 27.

### [Platform Engineering](https://www.plushcap.com/trends/monthly/platform-engineering?source=youtube)

Internal developer platforms and platform engineering

Monthly normalized mentions: 2026-07-01: 39; 2026-08-01: 43; 2026-09-01: 53.
Review total: 135; previous-quarter total: 157; quarter-over-quarter: -14.0%.
Distinct publishing companies across review quarter: 35.

### Growing trends and sustained momentum

Largest absolute quarterly gains: MCP, Voice AI, Observability, AI Model Fine-tuning. Absolute figures and baselines appear above.
Sustained review-quarter risers: none supported by contiguous monthly baselines.

### Recent momentum: 2026-08-01 through 2026-10-31

This rolling three-completed-month window overlaps the review quarter; it is not a new calendar-quarter result.

- AI Agents: 2026-08-01: 720; 2026-09-01: 873; 2026-10-01: 1,193; window total: 2786.
- MCP: 2026-08-01: 667; 2026-09-01: 813; 2026-10-01: 1,122; window total: 2602.
- Observability: 2026-08-01: 507; 2026-09-01: 604; 2026-10-01: 528; window total: 1639.
- LLM: 2026-08-01: 422; 2026-09-01: 542; 2026-10-01: 572; window total: 1536.
- Real-time: 2026-08-01: 308; 2026-09-01: 297; 2026-10-01: 421; window total: 1026.
- AI Coding Assistant: 2026-08-01: 263; 2026-09-01: 262; 2026-10-01: 409; window total: 934.
- Voice AI: 2026-08-01: 166; 2026-09-01: 336; 2026-10-01: 511; window total: 1013.
- Kubernetes: 2026-08-01: 139; 2026-09-01: 175; 2026-10-01: 215; window total: 529.
- AI Model Fine-tuning: 2026-08-01: 114; 2026-09-01: 37; 2026-10-01: 65; window total: 216.
- Platform Engineering: 2026-08-01: 43; 2026-09-01: 53; 2026-10-01: 85; window total: 181.

Sustained recent risers: Platform Engineering: mentions increased for three consecutive months.

## Competitive-space context

Up to 12 spaces (slug order), top 3 core/important topics per space. Blog, all accounts; stored monthly rankings, not quarterly rankings. Rationales are existing public-safe evaluations, not company performance evidence.

- [AI agents](https://www.plushcap.com/competitive/spaces/ai-agents): 2026-10-01 through 2026-10-31; #1 LLM (core). Large language models are the core reasoning and interaction layer for most AI agents, directly shaping how developers build, evaluate, deploy, and operate them. Their relevance spans agent frameworks, tools, runtimes, orchestration,… Calculated: 2026-11-03T15:39:05.204470+00:00.
- [AI agents](https://www.plushcap.com/competitive/spaces/ai-agents): 2026-10-01 through 2026-10-31; #2 MCP (core). MCP is directly relevant to AI-agent products because it standardizes how agents discover and use tools, data sources, and services. Its interoperability benefits span agent frameworks, runtimes, security layers, and developer platforms,… Calculated: 2026-11-03T15:39:05.204490+00:00.
- [AI agents](https://www.plushcap.com/competitive/spaces/ai-agents): 2026-10-01 through 2026-10-31; #3 AI Agents (core). AI agents and agentic frameworks are directly central to this space, shaping core choices around orchestration, runtimes, tools, security, evaluation, and deployment. The trend spans much of the developer ecosystem and reflects a durable… Calculated: 2026-11-03T15:39:05.204364+00:00.
- [AI Model Inference Providers](https://www.plushcap.com/competitive/spaces/ai-model-inference-providers): 2026-10-01 through 2026-10-31; #1 LLM (core). LLMs are a core workload for AI inference providers, directly shaping model availability, API capabilities, pricing, performance, and developer platform selection across the market. Calculated: 2026-11-03T15:39:05.203093+00:00.
- [AI Model Inference Providers](https://www.plushcap.com/competitive/spaces/ai-model-inference-providers): 2026-10-01 through 2026-10-31; #2 AI Model Fine-tuning (core). Fine-tuning is a direct extension of inference offerings, letting developers customize model behavior, quality, cost, and deployment characteristics for production use cases. It remains a durable buying and platform-selection consideration… Calculated: 2026-11-03T15:39:05.203032+00:00.
- [AI Model Inference Providers](https://www.plushcap.com/competitive/spaces/ai-model-inference-providers): 2026-10-01 through 2026-10-31; #3 AI Agents (core). AI agents are a major and durable workload for model inference providers, driving developer demand for low-latency, reliable, scalable, and cost-effective API access. Agentic applications also increase the importance of tool calling,… Calculated: 2026-11-03T15:39:05.202968+00:00.
- [Containerized app hosting](https://www.plushcap.com/competitive/spaces/containerized-app-hosting): 2026-10-01 through 2026-10-31; #1 Kubernetes (core). Kubernetes is a foundational container orchestration technology that directly shapes deployment, scaling, networking, and operations choices for containerized application hosting. Its broad ecosystem and long-term enterprise adoption make… Calculated: 2026-11-03T15:39:05.203303+00:00.
- [Containerized app hosting](https://www.plushcap.com/competitive/spaces/containerized-app-hosting): 2026-10-01 through 2026-10-31; #2 Observability (core). Observability and distributed tracing are directly relevant to operating containerized applications, where distributed services, ephemeral workloads, and deployment complexity make diagnosis and performance management essential. The… Calculated: 2026-11-03T15:39:05.203350+00:00.
- [Containerized app hosting](https://www.plushcap.com/competitive/spaces/containerized-app-hosting): 2026-10-01 through 2026-10-31; #3 Secrets Management (core). Secrets and credentials management is a durable security requirement for deploying and operating containerized applications, affecting configuration, access control, and production safety. It is broadly relevant to developer platform… Calculated: 2026-11-03T15:39:05.203398+00:00.
- [GPU providers](https://www.plushcap.com/competitive/spaces/gpu-providers): 2026-10-01 through 2026-10-31; #1 LLM (core). LLMs are a primary workload for GPU providers, driving demand for training, fine-tuning, inference, model hosting, and high-performance cluster capacity. They strongly shape developer hardware, pricing, availability, networking, and… Calculated: 2026-11-03T15:39:05.204225+00:00.
- [GPU providers](https://www.plushcap.com/competitive/spaces/gpu-providers): 2026-10-01 through 2026-10-31; #2 Kubernetes (core). Kubernetes is durable core infrastructure for deploying, scaling, and operating GPU-backed workloads, especially training and inference services. It strongly affects platform compatibility, orchestration capabilities, and customer… Calculated: 2026-11-03T15:39:05.204215+00:00.
- [GPU providers](https://www.plushcap.com/competitive/spaces/gpu-providers): 2026-10-01 through 2026-10-31; #3 AI Model Fine-tuning (core). Fine-tuning is a core GPU workload that directly shapes infrastructure selection through accelerator availability, interconnects, storage, orchestration, pricing, and managed training tooling. It is broadly relevant across GPU providers… Calculated: 2026-11-03T15:39:05.204164+00:00.
- [Hosted backend infrastructure-as-a-service](https://www.plushcap.com/competitive/spaces/hosted-backend-infrastructure-as-a-service): 2026-10-01 through 2026-10-31; #1 Observability (core). Observability and distributed tracing are durable, high-impact capabilities for hosted backend platforms because they determine how developers diagnose performance, reliability, and production failures. They influence platform selection… Calculated: 2026-11-03T15:39:05.203599+00:00.
- [Hosted backend infrastructure-as-a-service](https://www.plushcap.com/competitive/spaces/hosted-backend-infrastructure-as-a-service): 2026-10-01 through 2026-10-31; #2 Serverless (core). Serverless and functions-as-a-service are central deployment and runtime models for hosted backend platforms, affecting architecture, cost, scaling, and developer workflow. The model is broadly relevant across the space and remains a… Calculated: 2026-11-03T15:39:05.203666+00:00.
- [Hosted backend infrastructure-as-a-service](https://www.plushcap.com/competitive/spaces/hosted-backend-infrastructure-as-a-service): 2026-10-01 through 2026-10-31; #3 LLM (core). LLM capabilities are increasingly central to application development, influencing demand for AI-ready compute, managed data services, deployment patterns, observability, and integrated backend APIs. The trend is broad and likely durable,… Calculated: 2026-11-03T15:39:05.203557+00:00.

## Sources and company evidence

- [Trend dashboard](https://www.plushcap.com/trends)
- [Monthly trend figures](https://www.plushcap.com/trends/monthly)
- [Competitive spaces](https://www.plushcap.com/competitive/spaces)
- [Find your company](https://www.plushcap.com/companies)
- [Dated leaderboards](https://www.plushcap.com/leaderboards)

For tracked companies, collect dated Blog/video publishing activity, official-company X and LinkedIn activity where your access allows it, YouTube audience growth, and associated Hacker News discussions. Compare the displayed periods. Leaderboard position gains do not identify the companies surpassed. Newly tracked companies may lack historical coverage.

[Board-prep instructions and editable prompt](https://www.plushcap.com/cmo).