your agent can search Twitter, Reddit, and GitHub for free - zero API keys, zero billing 😳 agent-reach is trending on github with 23K stars. it lets your AI agent read Twitter posts, browse Reddit threads, search GitHub repos, watch YouTube videos - all without paying for a single API subscription what your agent accesses for $0: - Twitter/X posts, profiles, and search - Reddit threads and comments - YouTube videos, metadata, and search - GitHub repos, issues, and profiles - 10 more platforms - all in one pip install what this replaces: - Twitter API: $100/mo for basic access - Reddit API: rate-limited free tier, expensive at scale - YouTube API: quota limits, pay for more - GitHub API: generous but still rate-limited why this matters: - most AI agents are blind to the internet because APIs cost money - this gives any agent real-time web access at zero marginal cost - perfect for research agents, content radar, competitive intel, market analysis how to set up (2 min): > pip install agent-reach > run: agent-reach doctor > connect it to your agent as a tool > done - your agent can now search the internet for free important: - uses direct parsing, not official APIs - no keys needed - works with claude code, cursor, aider, langchain, any agent framework - MIT licensed, fully open source - not for production web scraping at scale - use for agentic research and prototyping - 23K stars and trending - community vetted let your agent browse Twitter, Reddit, and GitHub for $0 while everyone else is paying $100 /mo for API access bookmark this before payying for extra api ↓ repo in comment

what is agent looping for the last two years we prompted agents one task at a time. that is starting to change instead of asking an agent to build the landing page and then driving every step yourself, you set up a loop that handles discovery, planning, the work, checking, and iterating until the goal is met looping is a setup you build. almost any agent harness can run it, it just depends on how you wire it up at its simplest, looping is one agent working on itself: > researches > drafts > checks the draft against a goal > fixes what is weak > runs that cycle again until the work clears the requirements you are not prompting each step anymore. the agent repeats the cycle for you the bigger version is a fleet looping. you give an orchestrator agent a goal, it breaks the goal into pieces, hands each piece to a specialist agent, and those specialists hand smaller jobs to their own subagents the whole tree keeps looping through discovery, planning, execution, and verification until the goal is met one agent looping is like a person redoing their own draft. a fleet looping is a whole team running a project end-to-end you create a goal, and the system runs the loop until it finishes within the reqs you set open and closed looping: OPEN LOOPING is exploratory. it still has conditions and a goal, but you give the agent or the fleet a wide space to move in. it can try different paths, discover things, build something you did not fully spec out this is the exciting end, it is what Peter and others are doing, and tbh it is where I want to spend more time the catch is cost, an open loop with real room to explore burns an insane amount of tokens. for the 90 percent of people without an unlimited budget it is not runnable yet, and pointed at projects with a loose standard it turns into a slop machine CLOSED LOOPING is bounded. a human designs the end-to-end path first: > clear goal > defined steps > an eval at each step > a point where it stops or hands back to you (and feeds back performance data) the agents still loop, but inside framework you built. it gets better every run because each pass feeds the next, and it runs on a normal budget because the path is tight. for most marketing work, closed is the one that pays off today. > the orchestrator owns the goal > the specialists own the steps > the subagents do the narrow work > an eval gate make sure its not slop

🎯 Andrej Karpathy on how to learn.

Ok now that tokenmaxxing is starting to get its fair share of criticism properly.... imagine reading this exchange all over again. 😅 "you are not a good engineering company unless you can convince me that your engineers are burning infinite tokens"