Tales From the Trench: Building With LLMs and Honeycomb
Blog post from Honeycomb
The author undertakes a weekend challenge to create an AI application using Claude Code, aiming to develop a Slack chatbot that utilizes Redis Vector Sets for text embeddings. The project involves using Claude Code for most of the development, including testing, CI/CD, and deployment, with the author providing direction while staying within the CLI. The application, named phiLLM, is designed to read messages from a specific Slack user, build embeddings to generate an AI twin, and respond to queries. Throughout the process, the author encounters challenges like managing Redis versions, optimizing performance, and ensuring proper telemetry, but ultimately succeeds in deploying the app on AWS with Claude's assistance. The author reflects on the benefits and limitations of using AI for development, emphasizing the importance of clear specifications, fast feedback loops, and the potential of AI to enhance coding efficiency.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 40 | 1,743 | 309 | 141 | -2% |
| LLM | 8 | 4,627 | 710 | 226 | -2% |
| Observability | 8 | 2,182 | 516 | 159 | +14% |
| OpenTelemetry | 4 | 362 | 61 | 37 | -20% |
| RAG | 3 | 1,320 | 205 | 95 | +24% |
| Secrets Management | 2 | 1,440 | 222 | 88 | +5% |
| AI Agents | 1 | 2,249 | 530 | 180 | -12% |
| MCP | 1 | 3,727 | 385 | 128 | -5% |
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