We send the question + a compact JSON summary of the user's profile to Llama 3.3 70B (via Groq for latency — <400ms P95). The system prompt forces a specific output format: {answer: "3", confidence: 0.9} for numeric inputs, {answer: "Yes"} for booleans. Confidence < 0.7 means the bot skips the question (asks the user next session), rather than lie to LinkedIn. - Source: dev.to / about 1 month ago

This is the architecture post-mortem. I built it on weekends. It runs in Docker. It cost me exactly $0 in LLM credits during development because Groq's free tier is generous and Ollama works as a swap-in. The repo is here — issues and PRs welcome. - Source: dev.to / about 2 months ago

Intelligence Engine: Groq API (Utilizing Llama-3-70b for lightning-fast inference). - Source: dev.to / 3 months ago

A Python-based AI customer support agent that retains memory across sessions using Hindsight — an agent memory system built by Vectorize. The agent runs on Groq for fast, free LLM inference. - Source: dev.to / 3 months ago

What limits LLM inference accelerators? I heard about Groq (https://groq.com/) not sure how much it pushes away the problem. - Source: Hacker News / 4 months ago

I wired it into OpenCode, an open-source coding harness similar to Claude Code and Codex. I'm using an OpenCode Zen key and a Gemini key, and together, these give me access to multiple SOTA models for free, without touching a separate dashboard for each provider. - Source: dev.to / 7 days ago

I drove it from my coding-agent with a handful of commands. - Source: dev.to / 9 days ago

Https://pi.dev/docs/latest/providers#openai-codex is specific that it "Requires ChatGPT Plus or Pro subscription". https://opencode.ai are also both specific that it's for "Plus/Pro" subscriptions. Is there some link where you saw free tier Codex use in non-official apps is allowed by OpenAI? (I have used the free tier in the official Codex app, but as you said, labs can have different rules for official vs... - Source: Hacker News / 13 days ago

Https://opencode.ai/ OpenCode was the first agent harness I used, and I have always like it. You can configure a wide variety of providers, but it's open source and has a number of core contributors. The other opinionated option is Pi (the Pi agent harness). This is a great lightweight option and also supports a number of providers. You can also use local model servers. - Source: Hacker News / about 1 month ago

OpenCode with GLM 5.2 wrote custom Emacs Lisp to pinpoint within the file where the missing or extra bracket could be. It rewrote the custom code to check various parts of the file. Each of those is a tool use and many, many tokens burned. The next step is to turn those custom scripts written by the AI agent into a tool to speed up the process, or a skill that shows how to use other tools to speed up the process. - Source: dev.to / about 1 month ago