How to choose your coding agent: the decision in four questions
Guide to choosing a coding agent with judgment: what you already pay for, terminal or IDE, your real budget and how to test without marrying anyone.
The best AI tools for developers
AI for developers: unified model APIs, inference infrastructure, chatbots over your own documents and API observability. We compare usage-based pricing and ease of integration.
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What exactly do you want to do
There is no single «best AI» in this category, because it holds tools nobody would put side by side to choose between. Each block below is a different decision, and that is where we compare.
10
Terminal agents
Which terminal agent can I hand a task to and have it finish the whole thing?
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5AI editors
Which editor lets me write code with the AI built in, without switching tools?
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5IDE assistants
Which extension adds AI to the editor I already use, without migrating?
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5Autonomous agents
Which agent can pick up an issue and open the pull request without me watching?
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5App builders
What can I use to build a working app by describing it, without knowing how to code?
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5Review and quality
What can I add to my repo to review pull requests and catch bugs before I do?
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5Model APIs and platforms
Where do I call the models from inside my own product, and what does it cost per thousand calls?
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Comparison table
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Practical guides on Code
How to give your coding agents product memory with PaellaDoc
Guide to solving context lost between sessions: from the instructions file to PaellaDoc's local factory with memory, gates and evidence.
How to review AI-generated code without anything slipping through
Guide to reviewing agent code: the three-pass technique, CodeRabbit as first filter and the typical failures AI commits with confidence.
Security of AI-generated code: the pass that admits no shortcuts
Security guide for agent code: the typical failures AI introduces, directed review, secrets and dependencies, and what to automate.
Your first project with coding agents: the complete system
Guide to building your agent workflow: the instructions file, calibrating what to delegate, review with a net and the habits separating success from scares.
How to build an application without knowing how to code, sensibly
Guide to building with AI without code: choosing between Lovable, Bolt and Replit, iterating without burning credits and knowing when to eject to code.
How to work with several coding agents in parallel
Guide to parallel agent work: slicing independent tasks, orchestrating with Conductor or Codex's cloud and not dying in review.
How to run migrations and batch tasks with coding agents
Guide to batch work with AI: the pilot that defines the pattern, scaling with Devin or Conductor and verifying twenty changes without reviewing twenty.
What coding with AI really costs (and how to pay less)
Guide to coding agents' real cost: the map from free to intensive, the two-agent strategy and the patterns that blow up the bill.
How to automate your daily work with free CLI agents
Guide to automating with free agents: Gemini CLI and OpenCode in scripts and scheduled tasks, Goose for flows that cross tools.
Frequently asked questions
What is AIML API and who is it for?
A gateway that unifies hundreds of models (text, image, audio) behind a single OpenAI-compatible API. Built for developers who want to switch models without rewriting integrations.
When should I choose Baseten over self-hosting a model?
When you need reliable production inference without maintaining GPUs: Baseten scales, monitors and bills per usage. For experimenting, its free starting credits are enough.
Is FastGPT free?
The code is open source and free to self-host; the managed cloud has usage-based paid plans. It is one of the cheapest ways to build a chatbot over your own documents.
What does Akita add to my API?
Automatic observability: it detects endpoints, errors and latencies by watching traffic, with no invasive agents or manual instrumentation. Useful for teams inheriting undocumented APIs.
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