PettyUI/.firecrawl/apis-for-ai.md
Mats Bosson db906fd85a Fix linting config and package fields
- Replace .eslintrc.cjs with eslint.config.mjs (ESLint 9 flat config)
  using direct eslint-plugin-solid + @typescript-eslint/parser approach
- Add @typescript-eslint/parser to root devDependencies
- Add main/module/types top-level fields to packages/core/package.json
- Add resolve.conditions to packages/core/vite.config.ts
- Create packages/core/tsconfig.test.json for test type-checking
- Remove empty paths:{} from packages/core/tsconfig.json
2026-03-29 02:35:57 +07:00

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Jack Wallen](https://thenewstack.io/pihole-docker-network-adblocking/)
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Mar 20th 2026 7:00am, by \\
Reza Ramezanpour](https://thenewstack.io/kubernetes-network-security-hierarchies/)
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Mar 4th 2026 10:26am, by \\
Adrian Bridgwater](https://thenewstack.io/gsma-open-gateway-developers/)
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Feb 6th 2026 8:00am, by \\
Jack Wallen](https://thenewstack.io/how-homepage-simplifies-monitoring-your-self-hosted-services/)
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Feb 2nd 2026 4:00am, by \\
Max Liu](https://thenewstack.io/tidb-x-open-source-database/)
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Mar 18th 2026 5:00am, by \\
Motiejus Jakštys](https://thenewstack.io/btrfs-petabyte-cost-reduction/)
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Mar 17th 2026 9:00am, by \\
Tiago Castro](https://thenewstack.io/kubevirt-live-migration-mayastor/)
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Feb 2nd 2026 4:00am, by \\
Max Liu](https://thenewstack.io/tidb-x-open-source-database/)
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Jan 28th 2026 7:00am, by \\
Cynthia Dunlop](https://thenewstack.io/agodas-secret-to-50x-scale-getting-the-database-basics-right/)
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Jan 27th 2026 6:15am, by \\
Steven J. Vaughan-Nichols](https://thenewstack.io/chainguard-emeritoss-backs-minio-other-orphaned-projects/)
[AI](https://thenewstack.io/ai/) [AI Engineering](https://thenewstack.io/ai-engineering/) [API Management](https://thenewstack.io/api-management/) [Backend development](https://thenewstack.io/backend-development/) [Data](https://thenewstack.io/data/) [Frontend Development](https://thenewstack.io/frontend-development/) [Large Language Models](https://thenewstack.io/llm/) [Security](https://thenewstack.io/security/) [Software Development](https://thenewstack.io/software-development/) [WebAssembly](https://thenewstack.io/webassembly/)
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Mar 25th 2026 4:36am, by [Meredith Shubel](https://thenewstack.io/author/mshubel/ "Posts by Meredith Shubel")
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Mar 24th 2026 6:00am, by [Darryl K. Taft](https://thenewstack.io/author/darryl-taft/ "Posts by Darryl K. Taft")
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Mar 23rd 2026 11:00am, by [Jessica Wachtel](https://thenewstack.io/author/jessica-wachtel/ "Posts by Jessica Wachtel")
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Mar 23rd 2026 5:00am, by [Camille Crowell-Lee](https://thenewstack.io/author/camille-crowell-lee/ "Posts by Camille Crowell-Lee") and [Morgan Fine](https://thenewstack.io/author/morgan-fine/ "Posts by Morgan Fine")
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Mar 12th 2026 1:22pm, by [Charles Humble](https://thenewstack.io/author/charles-humble/ "Posts by Charles Humble")
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Mar 4th 2026 10:26am, by [Adrian Bridgwater](https://thenewstack.io/author/adrian-bridgwater/ "Posts by Adrian Bridgwater")
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Feb 17th 2026 9:37am, by [Charles Humble](https://thenewstack.io/author/charles-humble/ "Posts by Charles Humble")
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Jan 15th 2026 1:00pm, by [Heather Joslyn](https://thenewstack.io/author/hjoslyn/ "Posts by Heather Joslyn")
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Dec 24th 2025 8:00am, by [Sheldon Pereira](https://thenewstack.io/author/sheldon-pereira/ "Posts by Sheldon Pereira") and [Denton Chikura](https://thenewstack.io/author/denton-chikura/ "Posts by Denton Chikura")
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Dec 3rd 2025 1:00pm, by [Zziwa Raymond Ian](https://thenewstack.io/author/zziwa-raymond/ "Posts by Zziwa Raymond Ian")
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Aug 18th 2025 10:34am, by [Janakiram MSV](https://thenewstack.io/author/janakiram/ "Posts by Janakiram MSV")
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Mar 25th 2026 7:39am, by [Frederic Lardinois](https://thenewstack.io/author/frederic-lardinois/ "Posts by Frederic Lardinois")
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Mar 15th 2026 7:00am, by [Paul Sawers](https://thenewstack.io/author/paul-sawers/ "Posts by Paul Sawers")
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Feb 24th 2026 2:07pm, by [Paul Sawers](https://thenewstack.io/author/paul-sawers/ "Posts by Paul Sawers")
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Mar 17th 2026 11:50am, by [David Eastman](https://thenewstack.io/author/david-eastman/ "Posts by David Eastman")
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Mar 3rd 2026 10:21am, by [Jelani Harper](https://thenewstack.io/author/jelani-harper/ "Posts by Jelani Harper")
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Mar 3rd 2026 9:00am, by [Frederic Lardinois](https://thenewstack.io/author/frederic-lardinois/ "Posts by Frederic Lardinois")
[Meta gave React its own foundation. But it's not letting go just yet.](https://thenewstack.io/react-foundation-open-source-governance/)
Mar 3rd 2026 4:00am, by [Paul Sawers](https://thenewstack.io/author/paul-sawers/ "Posts by Paul Sawers")
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Jan 30th 2026 6:22pm, by [Steve Corndell](https://thenewstack.io/author/steve-corndell/ "Posts by Steve Corndell")
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Mar 25th 2026 4:00am, by [Oladimeji Sowole](https://thenewstack.io/author/oladimeji-sowole/ "Posts by Oladimeji Sowole")
[IBM, Red Hat, and Google just donated a Kubernetes blueprint for LLM inference to the CNCF](https://thenewstack.io/llm-d-cncf-kubernetes-inference/)
Mar 24th 2026 8:20am, by [Steven J. Vaughan-Nichols](https://thenewstack.io/author/sjvn/ "Posts by Steven J. Vaughan-Nichols")
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Mar 14th 2026 5:00am, by [Janakiram MSV](https://thenewstack.io/author/janakiram/ "Posts by Janakiram MSV")
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Mar 11th 2026 9:37am, by [Jennifer Riggins](https://thenewstack.io/author/jennifer-riggins/ "Posts by Jennifer Riggins")
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Mar 25th 2026 5:00am, by [Darryl K. Taft](https://thenewstack.io/author/darryl-taft/ "Posts by Darryl K. Taft")
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Mar 24th 2026 9:01am, by [B. Cameron Gain](https://thenewstack.io/author/bruce-gain/ "Posts by B. Cameron Gain")
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Mar 24th 2026 3:00am, by [Adrian Bridgwater](https://thenewstack.io/author/adrian-bridgwater/ "Posts by Adrian Bridgwater")
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Mar 22nd 2026 7:00am, by [Darryl K. Taft](https://thenewstack.io/author/darryl-taft/ "Posts by Darryl K. Taft")
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Mar 21st 2026 8:45am, by [B. Cameron Gain](https://thenewstack.io/author/bruce-gain/ "Posts by B. Cameron Gain")
[Why online stores keep showing the wrong products — and why tensors fix it](https://thenewstack.io/tensor-ranking-product-discovery/)
Mar 25th 2026 6:00am, by [Tim Young](https://thenewstack.io/author/tim-young/ "Posts by Tim Young")
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Mar 22nd 2026 6:00am, by [David Cassel](https://thenewstack.io/author/destiny/ "Posts by David Cassel")
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Mar 19th 2026 11:37am, by [TNS Staff](https://thenewstack.io/author/tns-staff/ "Posts by TNS Staff")
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Mar 19th 2026 11:01am, by [Adrian Bridgwater](https://thenewstack.io/author/adrian-bridgwater/ "Posts by Adrian Bridgwater")
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Mar 19th 2026 8:00am, by [Michele Mancioppi](https://thenewstack.io/author/michele-mancioppi/ "Posts by Michele Mancioppi")
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Mar 24th 2026 9:01am, by [B. Cameron Gain](https://thenewstack.io/author/bruce-gain/ "Posts by B. Cameron Gain")
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Mar 3rd 2026 2:00pm, by [B. Cameron Gain](https://thenewstack.io/author/bruce-gain/ "Posts by B. Cameron Gain")
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Feb 25th 2026 11:00am, by [Jessica Wachtel](https://thenewstack.io/author/jessica-wachtel/ "Posts by Jessica Wachtel")
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Feb 22nd 2026 6:00am, by [Jessica Wachtel](https://thenewstack.io/author/jessica-wachtel/ "Posts by Jessica Wachtel")
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Feb 7th 2026 9:00am, by [Jessica Wachtel](https://thenewstack.io/author/jessica-wachtel/ "Posts by Jessica Wachtel")
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Mar 25th 2026 7:14am, by
Jennifer Riggins
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Mar 25th 2026 4:00am, by
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Mar 20th 2026 6:00am, by
Ted Young
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Mar 19th 2026 5:00am, by
Sachi Desai
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Mar 17th 2026 7:00am, by
Yuval Fernbach
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Mar 26th 2026 7:00am, by
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Feb 22nd 2026 8:00am, by
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Jan 29th 2026 11:00am, by
Arjun Iyer
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Jan 27th 2026 6:00am, by
Joab Jackson
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Jan 26th 2026 11:00am, by
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Mar 15th 2026 5:00am, by
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Mar 12th 2026 6:00am, by
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Mar 8th 2026 6:00am, by
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Feb 24th 2026 2:07pm, by
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Feb 19th 2026 12:47pm, by
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Mar 5th 2026 2:29pm, by
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Feb 26th 2026 7:28am, by
Katie Greenley
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Feb 24th 2026 9:00am, by
Oleg Danilyuk
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Feb 24th 2026 4:00am, by
Justyn Roberts
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Feb 19th 2026 1:46pm, by
Ariel Russo
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Mar 25th 2026 8:43am, by
TNS Staff
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Mar 24th 2026 8:38am, by
B. Cameron Gain
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Mar 24th 2026 8:20am, by
Steven J. Vaughan-Nichols
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Mar 21st 2026 8:45am, by
B. Cameron Gain
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Mar 20th 2026 9:00am, by
Danielle Cook
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Mar 20th 2026 6:00am, by
Ted Young
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Mar 19th 2026 8:00am, by
Michele Mancioppi
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Mar 18th 2026 4:00am, by
Juraci Paixão Kröhling
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Mar 17th 2026 6:00am, by
TNS Staff
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Mar 16th 2026 7:04am, by
TNS Staff
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Mar 26th 2026 8:00am, by
Yevgeny Pats
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Mar 25th 2026 7:14am, by
Jennifer Riggins
[WebAssembly could solve AI agents' most dangerous security gap](https://thenewstack.io/webassembly-sandboxing-ai-agents/)
Mar 24th 2026 9:01am, by
B. Cameron Gain
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Mar 24th 2026 7:20am, by
Frederic Lardinois
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Mar 24th 2026 5:43am, by
Jack Wallen
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Mar 26th 2026 8:00am, by
Yevgeny Pats
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Mar 26th 2026 7:00am, by
Anirudh Ramanathan
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Mar 25th 2026 8:43am, by
TNS Staff
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Mar 18th 2026 8:02am, by
Jennifer Riggins
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Mar 17th 2026 4:00am, by
Eric Wang and Ying Zheng
[C++](https://thenewstack.io/c/) [Developer tools](https://thenewstack.io/developer-tools/) [Go](https://thenewstack.io/go/) [Java](https://thenewstack.io/java/) [JavaScript](https://thenewstack.io/javascript/) [Programming Languages](https://thenewstack.io/programming-languages/) [Python](https://thenewstack.io/python/) [Rust](https://thenewstack.io/rust/) [TypeScript](https://thenewstack.io/typescript/)
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Feb 5th 2026 12:00pm, by
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Nov 25th 2025 10:00am, by
Advait Patel
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Nov 23rd 2025 9:00am, by
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Oct 22nd 2025 2:00pm, by
Zziwa Raymond Ian
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Oct 15th 2025 7:05am, by
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Mar 20th 2026 7:33am, by
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2025-11-04 05:00:01
Its Time To Build APIs for AI, Not Just For Developers
contributed,
[AI Agents](https://thenewstack.io/category/ai-agents/) / [AI Engineering](https://thenewstack.io/category/ai-engineering/)
# Its Time To Build APIs for AI, Not Just For Developers
If your APIs were built for humans, they're probably failing AI agents. It's time for a paradigm shift to AI-first design.
Nov 4th, 2025 5:00am by [Saqib Jan](https://thenewstack.io/author/saqib-jan/ "Posts by Saqib Jan")
![Featued image for: Its Time To Build APIs for AI, Not Just For Developers](https://cdn.thenewstack.io/media/2025/10/35c6b952-agent-1024x576.jpg)
Image from Thapana\_Studio on Shutterstock.
For the last two decades, the [principles of API design](https://thenewstack.io/what-are-the-core-principles-of-good-api-design/) have centered around the human developer. We built systems optimized for their convenience, with flexible endpoints and rich [documentation](https://thenewstack.io/bad-documentation-bad-documentation/) that they could interpret.
But a new and powerful class of consumer is already disrupting in the form of autonomous [AI agents](https://thenewstack.io/ai-agents-a-comprehensive-introduction-for-developers/) that operate on a fundamentally different set of principles, which require a new approach to the way we build and describe our services.
“This means a new paradigm for us as developers: We must now build APIs optimized for consumption by machines, which requires a fundamentally different design philosophy than the one we use for human-centric development,” says [Srinivasan Sekar](https://in.linkedin.com/in/srinivasan-sekar), a director of engineering at [LambdaTest](https://www.lambdatest.com/), an AI-native software testing platform.
This increasing shift toward an “ [AI-first](https://thenewstack.io/ai-first-web-development-model-first-design-and-remix-v3/)” design philosophy prioritizes the explicit clarity and predictability that machines require to reason and act effectively. It underpins a clear framework for redesigning systems for the new agentic world.
## Shift From Developer-First to AI-First
At the heart of this new manifesto is a core cultural shift that must precede any architectural changes: moving from a “developer-first” to an [“AI-first” design](https://thenewstack.io/why-api-first-matters-in-an-ai-driven-world/). As Sekar explains, for years, we have optimized our APIs for the convenience of human developers.
This approach favors flexibility, often resulting in fewer, multipurpose endpoints and a reliance on external documentation to clarify ambiguity. A human developer can read a guide to understand that a certain parameter is required only when another is present — a nuance we have long taken for granted.
> “We must now build APIs optimized for consumption by machines, which requires a fundamentally different design philosophy than the one we use for human-centric development.”
>
> **— Srinivasan Sekar, director of engineering at LambdaTest**
AI agents, however, are fundamentally different consumers. They cannot read external documentation or infer implicit relationships between parameters. An AI operates solely on the explicit, machine-readable contract provided by the APIs schema. This, he argues, is the crux of the “AI-first” philosophy: a design approach that prioritizes the absolute, unambiguous clarity that machines require, leaving no room for interpretation in the contract.
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[Sai Krishna](https://www.linkedin.com/in/sai-krishna-3755407b/), working alongside Sekar, adds a practical dimension to this shift: “At LambdaTest, we learned this the hard way. We had a perfectly functional API for configuring test environments that developers loved for its flexibility. But when AI agents started using it, we saw a 40% failure rate because the agents couldnt interpret the implicit rules wed documented separately. We had to completely rethink our approach.”
This means favoring more specific, single-purpose endpoints and defining all constraints explicitly within the schema itself. This mindset is the non-negotiable foundation for [building any successful and reliable agentic system](https://thenewstack.io/agentic-ai-tools-for-building-and-managing-agentic-systems/).
## Unlearning the Three Habits of Human-Centric APIs
Adopting this “AI-first” philosophy in practice means actively unlearning several ingrained habits of traditional, human-centric API design. Sekar identifies three common patterns that, while convenient for human developers, create [critical failures when consumed by AI agents](https://thenewstack.io/no-apis-no-ai-why-api-access-is-critical-to-agentic-systems/).
First is the habit of overloading single endpoints with multiple behaviors. A developer can handle this flexibility, but an AI agent struggles with the ambiguity. The AI-first approach requires distinct, single-purpose endpoints where the function is explicit.
- **Before:** A single `POST /user` endpoint would ambiguously handle both creating and updating a user based on whether an `id` was present in the payload.
- **After:** The AI-first approach uses two distinct and predictable endpoints: `POST /users` to create a new user and `PUT /users/{id}` to update an existing one.
Second is the reliance on implicit contracts and external documentation. For an agent to act reliably, all parameter relationships and dependencies must be explicitly declared within the machine-readable schema itself.
- **Before:** A traditional schema would list `user_type` and `admin_level` as optional, forcing a developer to read external documentation to learn their conditional relationship.
- **After:** An AI-first schema makes this relationship explicit using conditional logic, allowing a machine to understand the contract without any external context.
Finally, teams must unlearn the habit of providing generic error responses. An AI-first API must provide structured, detailed error responses that allow an agent to self-correct.
- **Before:** A generic JSON response like `{"message": "Bad Request"}` would halt an automated workflow.
- **After:** A structured JSON error provides specific fields for the error `code`, `message` and `details`, indicating exactly which parameter was invalid.
These shifts share the common purpose of eliminating ambiguity. By making endpoints, contracts and errors explicit, developers provide the predictable foundation necessary for autonomous agents to act reliably and effectively.
## The New Pillars of AI-First Design
Beyond simply avoiding old habits, building an AI-first API requires embracing a new set of positive design principles centered on clarity and predictability.
“This begins with semantic clarity,” says [Sean Falconer,](https://www.linkedin.com/in/seanf/) senior director of product, AI strategy at [Confluent](https://www.confluent.io/). A truly AI-native API must do more than just describe its technical function; its machine-readable contract must also describe its business purpose, its prerequisites and any potential side effects. This provides the rich context an [AI agent needs to reason](https://thenewstack.io/4-reasons-agentic-ai-is-failing/) about not just how to use a tool, but when and why.
> A truly AI-native API must do more than just describe its technical function; its machine-readable contract must also describe its business purpose, its prerequisites and any potential side effects.
This means developers must enrich their API schemas, moving beyond simple data types. For example, in an OpenAPI specification, every parameter and endpoint should include a detailed description that explains not just the “what” (for instance, an integer ID), but the “why” (such as the unique customer identifier used for billing and support tickets).
This level of clarity is best achieved by designing what Falconer refers to as small, purpose-built tools rather than exposing large, generic API surfaces. [Yoni Michael](https://www.linkedin.com/in/yonimichael), CTO of [Typedef](https://www.typedef.ai/), agrees with this principle, advocating for a “minimal surface area,” meaning the API should expose only what is absolutely essential for a given task.
For architects, this translates into a clear design mandate: Resist the urge to create monolithic, all-purpose endpoints. Instead, complex business processes should be broken down into their smallest logical components, with a dedicated, constrained API designed for each one. A sprawling `/orders` API, for instance, could be refactored into focused, purpose-built tools like `/create-order`, `/check-order-status` and `/request-refund`. Creating these well-defined tools reduces ambiguity and the cognitive load on the AI, making its behavior easier to govern and evaluate.
All of these principles serve a single, critical goal: achieving what Michael calls deterministic behavior. An autonomous agent cannot afford surprises when it is chaining together multiple tools to execute a complex workflow. The system must be utterly reliable and predictable.
To deliver on this, engineers must prioritize rigorous testing and stateless design where possible. Every API call with the same inputs should consistently produce the same output, free from hidden dependencies or unpredictable side effects. This involves providing clear, idempotent interfaces for any operations that modify data, ensuring that repeated calls do not have unintended consequences.
By building APIs with semantic clarity, a minimal surface area and a clear purpose, architects provide the foundation of trust that allows an AI agent to build upon them effectively.
## Hurdles of Reshaping Data for AI
Even with these forward-thinking design principles in place, there is a final, deeper architectural challenge that underpins all AI-first design. Sekar from LambdaTest identifies this as the most significant hurdle of all: the difficult but necessary task of data model flattening.
He explains that most existing enterprise APIs reflect deep-rooted data platform challenges, as they were designed around complex internal database schemas or nested object models. While a human developer can navigate these intricate structures, they create significant “cognitive overhead” for an AI agent.
A deeply nested data structure forces an AI model to [expend valuable resources simply understanding](https://thenewstack.io/automating-context-in-structured-data-for-llms/) the shape of the data and the relationships between its parts before it can even begin to act on the information.
This complexity introduces a high potential for error and makes the agents behavior less predictable. The AI-first solution is to flatten and normalize these data models, redesigning them into simpler, more predictable formats that are optimized for machine consumption.
> “The companies building the most reliable agentic systems arent necessarily the ones with the most sophisticated AI models. Theyre the ones whove done the hard work of redesigning their API foundations to speak the language machines understand.”
>
> **— Srinivasan Sekar**
And this is usually the most resource-intensive part of the journey to becoming AI native. Sekar argues that this task goes far beyond simply documenting existing systems. It frequently requires a fundamental redesign of the data access layer and the creation of entirely new, parallel API surfaces that are purpose-built for AI agents.
Krishna shares the practical reality of this transformation: “We maintain two API layers now; our legacy developer API and our AI-optimized API. The AI version takes a test result object that was previously nested four levels deep and flattens it into a single-level structure with explicit relationship IDs. It tripled our schema size but cut agent processing time by 70%. The investment was significant, but necessary.” This ensures that the context provided to the AI is not just semantically clear, but also structurally simple and immediately useful.
## The Future Is a Behavioral Contract
Taken together, these principles — a cultural shift to an AI-first mindset, the unlearning of old habits and a deep architectural commitment to clarity and simple data models — form a new manifesto for API design. But the impact of this new philosophy extends beyond the initial engineering of our systems and into their entire life cycle.
Sekar predicts that this will ultimately reshape core DevOps practices like API versioning. In a world where autonomous agents are the primary consumers, the focus of API management will shift from tracking simple syntax changes to guaranteeing “behavioral contracts.” The promise to the AI will no longer be just that the APIs structure is stable, but that its behavior is consistent and predictable, ensuring the same inputs always produce the expected type of outcome.
Krishna elaborates on how this plays out operationally: “Weve started versioning our behavioral contracts separately from our API versions. An agent subscribes to a behavioral contract, say, search capability with pagination, and we guarantee that contracts behavior even as we evolve the underlying implementation. If we need to change behavior, we introduce a new contract version, giving agents time to adapt.”
Both Sekar and Krishna emphasize that this commitment to explicit, predictable and behaviorally consistent APIs is the ultimate expression of the AI-first philosophy.
“The companies building the most reliable agentic systems arent necessarily the ones with the most sophisticated AI models,” Sekar notes. “Theyre the ones whove done the hard work of redesigning their API foundations to speak the language machines understand.”
This foundation is what the next generation of reliable agentic AI applications will be built upon.
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