What an agent developer actually builds
An agent is a language model that calls tools in a loop. It decides on a step, runs a tool such as a search or a database query, reads the result, and decides what to do next. Anthropic's engineering guide says agents are usually just LLMs using tools based on feedback from their environment, so the hard part is designing the tools and their documentation well. The same guide separates workflows, where your code fixes the steps, from agents, where the model picks them.
Most of the job is ordinary software work: APIs, error handling, logging, tests and deployment. The model call is one function among many. Anthropic also advises finding the simplest solution first and adding complexity only when it helps, which sometimes means building no agent at all. Employers value people who can tell when a plain script or a single model call will do.
The skills, in the order to learn them
1. Software engineering. Write clean code in one language, use Git, write tests, and ship a small web service. Everything else rests on this. 2. APIs. Learn to call REST APIs, handle authentication, retries, rate limits and JSON. 3. Tool calling. OpenAI documents a five-step loop: send the request with tool definitions, receive a tool call, run the code in your application, send the result back, then get a final answer or more tool calls. Anthropic's docs describe the same round trip, where your code runs client tools and returns a tool_result block.
4. Orchestration. Learn the standard patterns Anthropic names: prompt chaining, routing, parallelization, orchestrator-workers and evaluator-optimizer. Add stopping conditions such as a maximum number of iterations. 5. Evaluation. Build a test set of real tasks and measure every change against it. 6. Safety. Study the OWASP Top 10 for LLM applications, which lists prompt injection first and also covers excessive agency. Test agents in sandboxed environments with guardrails, as Anthropic recommends, and add human checkpoints before risky actions.
Projects that show each skill
Tool calling: build a small assistant with two or three tools, for example a weather lookup and a calendar query, with JSON schemas for each input. Show how it handles a bad argument or a failed API call. Orchestration: build a routing workflow that sorts support tickets into categories and sends each to a specialized prompt, then a prompt chain with a code check between steps. Write a short note on why you chose a workflow over an open-ended agent.
Integration: expose a data source through a Model Context Protocol server. MCP is an open standard Anthropic released for connecting AI tools to data sources through servers and clients. Evaluation: publish a task set of 30 to 50 cases with pass rates before and after you changed a tool description. Safety: try indirect prompt injection against your own agent, using text planted in a document it reads, and document the defenses you added. A README with numbers beats a demo video.
Degrees, certifications and getting hired
No source we read says agent work requires a degree. For the broader software developer occupation, BLS says workers typically need a bachelor's degree in computer and information technology or a related field. Many agent developers arrive from backend or full-stack engineering roles, where they already know APIs and production systems. Certifications from cloud vendors can help you learn a platform, but they are not a substitute for working projects.
Read the official documentation of the model providers you use, because tool and model names change quickly. Anthropic's guidance on writing tools stresses giving each tool a clear, distinct purpose and returning only high-signal information to the agent. Showing that kind of judgment in your code review and project write-ups tells a hiring manager more than a list of frameworks.
Pay
USD a year, before tax. US figures from BLS OEWS May 2025, moved to 2026 with the Employment Cost Index; the US median is about $140,200. BLS has no AI or agent series, so this uses the nearest match, software developers, which covers the whole occupation, not agent specialists alone; employer, location and stock or bonus move actual pay. Refer to the AI Agent Developers salary guide for figures from live adverts.
What you need
- ProgrammingFluency in one general-purpose language, with Git, testing and debugging. This is the base for every later skill.
- API integrationComfort calling and building REST APIs, handling authentication, retries, timeouts and JSON payloads.
- Tool callingAbility to define tools with JSON schemas, run the model's tool calls in your own code and return results to the model.
- Orchestration patternsKnowing when to use chaining, routing, parallel calls, orchestrator-workers or evaluator loops, and how to set stopping conditions.
- EvaluationBuilding task sets and measuring success rates so you can tell whether a change helped.
- Security and safetyUnderstanding prompt injection, excessive agency and sensitive data exposure, and using sandboxes, guardrails and human approval steps.
How to get there
- Stage 1Learn software engineeringPick one language, write tested code, use Git and deploy a small web service.
- Stage 2Work with APIsCall third-party REST APIs and handle auth, errors, retries and rate limits.
- Stage 3Build tool-calling appsDefine tools with JSON schemas and implement the full request, tool call, result, answer loop.
- Stage 4Orchestrate workflowsBuild routing and chaining workflows, then a bounded agent loop with an iteration limit.
- Stage 5Add evaluationCreate a task set, track pass rates and use them to improve tools and prompts.
- Stage 6Harden for safetyTest prompt injection, restrict tool permissions, sandbox execution and add human checkpoints.
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Questions people ask
Do I need a degree to become an AI agent developer?
No source we read says agent work requires a degree. BLS says software developers typically need a bachelor's degree in computer and information technology or a related field, so a degree helps in that wider occupation. Strong public projects and engineering experience also count with many employers.
Is there a required certification or license for agent developers?
No. No regulator oversees AI agent development and no certification is required. Vendor certifications can help you learn a cloud platform, but they do not guarantee a job.
What is tool calling?
Tool calling, also called function calling, lets a model request that your code run a function you defined. Your application runs the function, sends the result back, and the model either answers or asks for another tool. It is the core mechanism behind agents.
Should I start with an agent framework?
Anthropic's guide says frameworks help you start quickly but recommends reducing abstraction layers and building with basic components as you move to production. Learning the raw API loop first makes frameworks easier to debug later.
How much do AI agent developers earn in the US?
BLS has no agent developer series. The nearest match, software developers, gives a 2026 US range of about $108,500 to $177,400 between the 25th and 75th percentiles, with a median near $140,200, for the whole occupation.
What is the biggest security risk in agents?
OWASP lists prompt injection first in its Top 10 for LLM applications, and excessive agency is also on the list. Agents that read untrusted text and can take actions need limited permissions, sandboxed testing and human approval for risky steps.
Sources
- Anthropic: Building effective agents
- OpenAI API docs: Function calling
- Claude Platform Docs: Tool use with Claude
- Anthropic: Writing effective tools for agents
- Anthropic: Introducing the Model Context Protocol
- AWS Prescriptive Guidance: Mapping to OWASP top 10 for LLM applications
- BLS Occupational Outlook Handbook: Software developers
