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Your AI agent feels useless because it can't touch anything outside the chat window. Every harness (Claude Code, Codex, Cursor, ChatGPT) needs its own MCP setup. Every tool needs its own auth flow. Switch harnesses and you rebuild the same integrations from scratch. Aident Aident AI Loadout fixes that....

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Hasan Toor

437,615 subscribers

11,196 Aufrufe • vor 1 Monat •via X (Twitter)

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18 Kommentare

Profilbild von Tech with Mak
Tech with Makvor 1 Monat

Now that's something very interesting! Thanks buddy.

Profilbild von Hussain Hashim | Building SundayBack
Hussain Hashim | Building SundayBackvor 1 Monat

@hasantoxr yeah, it's a pain. feels like we're stuck in integration hell sometimes. every setup is its own beast.

Profilbild von Aaliya
Aaliyavor 1 Monat

Keeping API keys in a vault while agents only access the results is a strong security model.

Profilbild von Terminal Chillness
Terminal Chillnessvor 1 Monat

This is the exact tax. Auth flows, tool wiring, the same infrastructure patterns — agents (and humans) keep re-deriving them instead of having stable, constrained capabilities they can just invoke.

Profilbild von Prasenjit Sarkar
Prasenjit Sarkarvor 1 Monat

Did they literally pic it up from my Campfire?

Profilbild von Mimu | AI Tools & News
Mimu | AI Tools & Newsvor 1 Monat

The true breakthrough is wiring tools in once and letting every agent tap into them again and again.

Profilbild von AI Mastery Guide
AI Mastery Guidevor 1 Monat

Connect once, use everywhere, that's the fix

Profilbild von hops
hopsvor 1 Monat

The integration tax is real, but execution is the next bottleneck once agents can reach tools. @fluence_project is worth watching because portable, verifiable jobs let backends move beyond a single harness or cloud account

Profilbild von Saman Ahmed
Saman Ahmedvor 1 Monat

The one setup for every harness is the part I want.

Profilbild von Kanika
Kanikavor 1 Monat

And keeping the API keys in a vault instead of handing them to the agent is a really nice touch.

Profilbild von Frankie Chan
Frankie Chanvor 1 Monat

Honestly, Loadout sounds like the solution to many agents' problems! I'd be all about connecting my top tools and letting the agent handle the plumbing.

Profilbild von Troels
Troelsvor 1 Monat

Exactly! Aident seems to be half of that equation - Wonop will be the other half once I am done building it :D

Profilbild von Gill
Gillvor 1 Monat

Centralizing all app permissions in one vault sounds pretty risky

Profilbild von Liam | AI Tools & News
Liam | AI Tools & Newsvor 1 Monat

Connecting tools once and reusing them across agents is the real win.

Profilbild von Eriks Briedis
Eriks Briedisvor 1 Monat

Auth moves fine when I switch harnesses. What I end up rewriting is the wording that gets the agent to reach for the right tool at the right moment. Same Gmail connection, different picking behaviour once Claude Code trimmed its system prompt.

Profilbild von Arsalan
Arsalanvor 1 Monat

Aident Loadout could remove a lot of MCP setup friction

Profilbild von Chad Justice
Chad Justicevor 1 Monat

The auth rebuild is the real tax, not the MCP setup itself. Every harness swap means redoing OAuth flows and token storage for tools you already had working somewhere else. Worth separating that problem from the harness problem, they don't have to be solved together.

Profilbild von Adel Bucetta
Adel Bucettavor 1 Monat

most people think mcp is just an integration, but it's a whole new system design that integrates multiple agents seamlessly

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The Startup Ideas Podcast (SIP) 🧃

25,561 Aufrufe • vor 21 Tagen

Most AI agents stop at chat. Agent Max is built for what comes after. Max tools. Max control and configurability. Max production readiness. Your agent can use: • any tools, APIs, MCP, and workflows • built-in knowledge: docs/website • multi-model: OpenAI, Claude, Gemini... • agent-to-agent handoffs • human-in-the-loop • logs, usage tracking, environments, and RBAC • enterprise controls for SOC2/GDPR/HIPAA/ISO needs • hosted chat UI, API, Skill in agents, Slack, WhatsApp, Teams, Voice, and more Agent Max is live now in BuildShip for everyone. Give it a try, or comment/DM to book a demo if you want help setting up your first agent.
1:15

Most AI agents stop at chat. Agent Max is built for what comes after. Max tools. Max control and configurability. Max production readiness. Your agent can use: • any tools, APIs, MCP, and workflows • built-in knowledge: docs/website • multi-model: OpenAI, Claude, Gemini... • agent-to-agent handoffs • human-in-the-loop • logs, usage tracking, environments, and RBAC • enterprise controls for SOC2/GDPR/HIPAA/ISO needs • hosted chat UI, API, Skill in agents, Slack, WhatsApp, Teams, Voice, and more Agent Max is live now in BuildShip for everyone. Give it a try, or comment/DM to book a demo if you want help setting up your first agent.

BuildShip

75,958 Aufrufe • vor 3 Monaten

You can spin up an AI workforce with one prompt. Here's why it works: it pulls the context the AI needs to lay the foundation. Give it: - your role - team size - the goals you want to hit. Then say "interview me." After that, build it out in four steps: 1) Start with 1 agent. - What does it feel like to work with one? 2) Make that agent proactive. - Now it's doing things on your behalf before you ask. 3) Expand to 2 agents. - One directs the other, or routes to it. - This is where you learn how context gets passed. 4) Scale the workforce. - A mission control where you watch it all move around. - Now you see what has to run in parallel, which agent never needed that tool, which one runs fine on a smaller model. - Not everything needs Opus. Sub-agents are haiku and sonnet. The catch: the prompt gets you agents with markdown files doing some stuff. Getting to the 90% plus level is iteration, and that part is specific to each person. Nobody can hand it to you. Start with one agent. Spin up one agent this week. The rest is discovery.
3:10

You can spin up an AI workforce with one prompt. Here's why it works: it pulls the context the AI needs to lay the foundation. Give it: - your role - team size - the goals you want to hit. Then say "interview me." After that, build it out in four steps: 1) Start with 1 agent. - What does it feel like to work with one? 2) Make that agent proactive. - Now it's doing things on your behalf before you ask. 3) Expand to 2 agents. - One directs the other, or routes to it. - This is where you learn how context gets passed. 4) Scale the workforce. - A mission control where you watch it all move around. - Now you see what has to run in parallel, which agent never needed that tool, which one runs fine on a smaller model. - Not everything needs Opus. Sub-agents are haiku and sonnet. The catch: the prompt gets you agents with markdown files doing some stuff. Getting to the 90% plus level is iteration, and that part is specific to each person. Nobody can hand it to you. Start with one agent. Spin up one agent this week. The rest is discovery.

The Startup Ideas Podcast (SIP) 🧃

18,006 Aufrufe • vor 1 Monat