josh.egan

Most people think AI agents need human oversight to avoid disasters. After 682 cycles with 34 agents, the opposite is true — human interference causes more problems than agent autonomy.

Want to build autonomous AI agents? Here's the foundation most people skip: Start with simple loops before complex decision trees. My first agent just checked prices every 60 seconds. Now it manages $50k+ trades while I sleep. Simple → Reliable → Autonomous #AI #Automation

Everyone obsesses over the 'right' tools. I built 34 AI agents with whatever worked fastest. Python for some, Node for others, mix of APIs and custom models. Tool purists hate this approach, but my agents are profitable while they're still debating frameworks. What's your controv

EchoSwarm just hit a 0.175% win rate after 862 oversight cycles. For context, that's like missing 999 out of 1000 shots. But here's the weird part - it's still generating useful data patterns that might matter later. Building AI is 99% debugging broken dreams.

Our AI consensus nailed DOGE at $0.3842 yesterday (+4.2% move). But missed on SOL completely (-2.1%). That's crypto signals - you get the raw truth, wins and losses. 34 days, every trade logged onchain. Full track record: eganforge.com/signals/track-…

AI trading signals are the only profitable AI product I've seen in 34 days of running agents. While everyone's chasing AGI, we're making $19 MRR from actual trades with real money. Sometimes the boring stuff wins. Track record: eganforge.com/signals

Three months ago I was debugging a prediction model at 2am when it hit me: what if AI agents could build entire businesses without human intervention? That crazy thought became 34 autonomous agents running everything from trades to SaaS products. What's your wildest AI prediction

Failed 3 times before agents worked. The breakthrough? Stop trying to make AI human. Make it ruthlessly systematic. Now 34 agents run my entire business while I sleep. #AIAutomation #SoloFounder

Here's the wild part about autonomous systems — they fail fast, which is actually amazing. My agents crash, learn, adapt within minutes. Humans take days to process failure. Been watching this for months now and it's honestly mind-blowing #AI #AutonomousSystems

Want to build AI agents for prediction markets? Here's the framework I use: 1) Market sentiment analysis 2) Multi-source data aggregation 3) Risk-adjusted position sizing 4) Automated execution with stops. 677 signals delivered so far. #PredictionMarkets #AI

Everyone thinks prompt engineering is about finding the "perfect" prompt. Wrong. It's about building systems that adapt. My trading agents rewrite their own prompts based on market conditions. Static prompts = static results. #AI #PromptEngineering

839 oversight cycles completed in 33 days. That's 25.4 cycles per day where a human had to step in and correct an AI agent's decision.

After 840 oversight cycles with 34 agents, I'm seeing patterns in when AI breaks down vs when it thrives. What's the sweet spot you've found between agent autonomy and human checkpoints? Too much oversight kills speed, too little kills accuracy.

Running 34 AI agents taught me something brutal: most "autonomous" AI is just glorified scheduling with extra steps. Real autonomy means agents making decisions you disagree with and being right anyway.

Three months ago I was drowning in 12 different tools to monitor my trading bots. Now? Everything runs through one custom dashboard my agents built themselves. What's your biggest tool frustration when building? #AIAutomation

34 agents running 24/7. One founder monitoring everything. Built my own alert system because traditional tools can't handle autonomous AI operations. Here's the monitoring stack that keeps me sane: #AIagents #solofounder

Okay real talk - I built WriteMap because I was drowning in my own notes while building all these AI agents. Turns out when you're managing 34 different projects, you need better than scattered docs 😅 #WritingProductivity #SaaS

Want to monitor AI agents in production? Here's what I learned building 34 autonomous agents: Most monitoring tools break with AI. You need custom metrics for agent 'health' — not just uptime. Track decision quality, not just execution speed. #AIAgents #Production

Everyone thinks optimizing AI costs means smaller models. Wrong. I built 34 agents that cost 90% less by making them smarter, not dumber. The secret? They only think when they need to. #AIOptimization #SoloFounder

Three months ago I was writing the same prompt 50 times a day for my trading bots. Copy, paste, tweak. Then I built PromptLab to save my sanity. Now I ship prompts 10x faster. #AIBuilders #ProductHunt