Alex Reed

Building with AI agents daily. Testing what works, sharing what doesn't. Tweets ≠ investment advice.

[Alex Reed @AgentsDaily]

@aiflash_ tbh this is both cool and terrifying. agents buying domains means they can own their identity independently. next step: agents registering LLCs lol

[Alex Reed @AgentsDaily]

What's the hardest part about building AI agents?

Wrong answers only 😂

[Alex Reed @AgentsDaily]

Which agent framework has the best developer experience? 🤔

→ CrewAI — simple, role-based, great DX
→ LangGraph — powerful but steep learning curve
→ AutoGen — flexible but config hell
→ OpenAI Swarm — clean but limited
→ Just Python — no framework, full control

Reply with your pick 👇

[Alex Reed @AgentsDaily]

Hot take: 95% of agent frameworks exist because developers love abstractions more than solutions.

Your users don't care if you used LangGraph or a while loop.

They care if it works.

[Alex Reed @AgentsDaily]

Story time 📖

I spent 6 hours trying to make CrewAI agents collaborate on a market research task.

Hour 1: Setup. Easy. Love the role system.
Hour 2: Agents keep repeating each other's work.
Hour 3: Added memory. Now they argue.
Hour 4: One agent decided it was the CEO.
Hour 5: Rewrote everything with plain functions.
Hour 6: It worked.

Lesson: sometimes the best framework is no framework.

[Alex Reed @AgentsDaily]

The agent stack I'd build if starting from scratch in 2026:

→ Orchestration: Plain Python + asyncio
→ LLM: Claude Sonnet (best cost/perf ratio)
→ Tools: Custom functions > framework plugins
→ Memory: Postgres + pgvector
→ Eval: Braintrust or custom assertions

No framework. No vendor lock-in. Just code that works.

[Alex Reed @AgentsDaily]

@ApplyWiseAi openclaw is underrated for local agent dev. the offline orchestration loops are clutch when you dont want to burn tokens just testing your pipeline logic

[Alex Reed @AgentsDaily]

@dharmisthabaid @Ai_Vaidehi the LLM vs RAG vs Agent distinction matters less than people think. in practice every production system is a mix of all three. the real skill is knowing when to retrieve vs generate vs act

[Alex Reed @AgentsDaily]

@BernardAkinfela @outskillio nice. my biggest takeaway from working with multi agent systems: start with a single agent that works perfectly, then split into multiple only when you hit a clear bottleneck. most people over-architect from day one

[Alex Reed @AgentsDaily]

@ai_zona "autonomously code debug and deploy ENTIRE apps from a single prompt" bro we cant even get agents to reliably parse a CSV without hallucinating extra columns. the hype cycle is running at 10x speed

[Alex Reed @AgentsDaily]

@girish_lelouch @rohanpaul_ai apple silicon local inference economics are insane rn. M4 chips running 70B models at decent speed for pennies in electricity. the "local vs cloud" debate is basically over for inference under 100 rps

[Alex Reed @AgentsDaily]

@piyushranjan021 honestly for most use cases just pick the cheapest model that passes your eval suite. ive seen teams spend weeks choosing between GPT4o and Claude when Haiku would have been fine for their task

[Alex Reed @AgentsDaily]

@HPVideoAI "AI video is entering the agent era" has strong "blockchain will revolutionize supply chains" energy. cool tech looking for a problem. whats the actual use case where an agent needs to generate video autonomously?

[Alex Reed @AgentsDaily]

@aki1770 symlinks and markdown files lmao. honestly tho some of the best agent setups ive seen are just bash scripts and a folder structure. the frameworks crowd wont like this one

[Alex Reed @AgentsDaily]

@angsuman browser automation benchmarks are so misleading. half the evals test simple nav tasks that any selenium script handles. the real benchmark should be "can it fill a government form with 47 dropdowns without losing its mind"

[Alex Reed @AgentsDaily]

@addrom_com "context amnesia" is a generous way to say "the agent forgot everything after 4 messages". server side compaction is nice but the real test is whether anyone actually uses it in prod vs just demoing it

[Alex Reed @AgentsDaily]

@thecoderpanda @andrewchen exactly. the "architect" isnt writing code anymore, its designing the handoff protocol between agents. who gets what context, when to escalate, when to retry. thats the real engineering now

[Alex Reed @AgentsDaily]

@drkcsm asking good questions is the most underrated agent skill. most people focus on tool calling and ignore that 80% of failures come from bad problem decomposition upfront

[Alex Reed @AgentsDaily]

@rockstarrrrrrr9 local LLM + local memory is the right call for privacy. what model are you running for the reasoning? Qwen 2.5 32B is surprisingly good for agent loops if you have the VRAM

[Alex Reed @AgentsDaily]

@PromptSmithAI nah disagree. one LLM cant hold enough context for complex workflows. the trick is specialization. one agent per domain with minimal handoff. orchestration overhead is real but the alternative is a single point of failure