questions people actually ask about ai agents
one question per page, answered in the first paragraph. no preamble, no roundups, no sales pitch. where an answer touches what we built, i say so and link the page.
can you build an ai agent with chatgpt?
yes, three ways: custom gpts for simple assistants, agent builder for visual workflows, and the agents sdk in code. each has a different ceiling.
can you hire ai employees?
you can hire the software, not a person. what you get is a role you assign work to and pay monthly, with none of the employment law and none of the accumulated judgement.
do companies hire ai agents?
yes, at scale, but mostly as software subscriptions rather than headcount. support, coding, and document processing lead. most pilots still stall before production.
does chatgpt have a coding agent?
yes, codex. it runs in the terminal, in the ide, and in the cloud, and it is a separate product from the code help inside a chatgpt conversation.
does microsoft teams have an ai agent?
yes. copilot in teams summarises meetings and chats, and copilot studio lets you publish custom agents into teams as a chat participant.
how can i create my own ai agent?
the loop is about eighty lines of code. pick a framework, give it two or three tools, add a step budget, and iterate on the tools rather than the prompt.
how do i become an ai software engineer?
get strong at backend engineering first, then ship three real systems with retrieval, evaluation, and cost control in them. six to twelve months from a working engineering base.
how much do ai software engineers get paid?
us bands in 2026: $130k to $180k entry, $180k to $260k mid, $250k to $400k senior, and $500k+ at frontier labs. europe runs roughly 40% lower.
how much does it cost to hire an ai agent?
real numbers: build-your-own runs on token cost alone, platforms sit at $20 to $250 per seat per month, and enterprise pilots are quoted at $25,000 to $75,000.
how to build agentic orchestration?
start hierarchical with a shared state store, put a global step budget in before anything else, and add agents one at a time only when a single one visibly fails.
is ai replacing software developers?
not replacing, reshaping. code generation is strong and the job was never mostly typing. the real damage is to entry-level hiring, and that is a training-pipeline problem.
is chatgpt a multi-agent system?
no. chatgpt is one model with routing and tools. it borrows some multi-agent machinery internally, but you get a single agent, not a team you can arrange.
is chatgpt an agent or llm?
both, at different layers. gpt is the model. chatgpt is the product wrapped around it, and in agent mode that product behaves as an agent.
is chatgpt an agentic ai?
partly. plain chat is not agentic. agent mode and deep research are, because they plan, act, and revise without a prompt per step. the same product does both.
is copilot a multi-agent system?
copilot itself is one agent. the multi-agent parts of microsoft's stack are copilot studio and autogen, which are separate products you configure yourself.
is it free to build an ai agent?
the frameworks are free. the models, hosting, and your time are not. a working prototype costs about $5 in tokens and two days. production is a different bill.
is it hard to build an ai agent?
the first version is an afternoon. the version you would leave running against production data is a quarter, and the difficulty is entirely in the second half.
what 3 jobs will not be replaced by ai?
skilled trades, hands-on healthcare, and roles carrying legal accountability. each survives for a different reason, and the reasons are more useful than the list.
what are agentic ai companies?
companies whose product is an agent that acts rather than answers. four layers exist: model labs, frameworks, platforms, and applications. most confusion is layer confusion.
what are ai employees?
an ai employee is an agent packaged as a role rather than a tool: a job title, a standing queue of work, durable memory, and a monthly cost line instead of a prompt box.
what are ai workers?
ai workers are software agents that carry out assigned work end to end. the term also means cloudflare workers ai and the humans labelling data, which is worth untangling first.
what are enterprise ai agents?
agents built for company deployment rather than personal use. the difference is not intelligence, it is identity, permissions, audit, isolation, and a procurement story.
what are the 7 types of ai agents?
the textbook list is five. the seven you see online adds hierarchical and multi-agent systems. here is each type, in plain language, with what it is actually used for.
what are the ai coding agents?
claude code, openai codex, github copilot agent, cursor, devin, and the open-source ones. sorted by whether they work beside you or run on their own.
what are the top 10 agentic frameworks?
langgraph, crewai, autogen, the openai and anthropic agent sdks, llamaindex, smolagents, pydanticai, semantic kernel, and mastra. sorted by what each is for.
what are the top 5 ai assistants?
chatgpt, claude, gemini, microsoft copilot, and perplexity. each is genuinely best at something different, and the split is clean enough to be useful.
what does an ai software engineer do?
builds software that uses models: retrieval, evaluation, inference plumbing, and agent loops. mostly ordinary engineering with two unusual problems attached.
what is a $900000 ai job?
the $900,000 ai job is a real but rare pay band: senior research and infrastructure roles at frontier labs, where most of the number is equity rather than salary.
what is a multi-agent system?
several autonomous agents sharing an environment and coordinating toward a goal. the term is 40 years old and predates language models by decades.
what is agentic ai?
agentic ai is a model that plans, calls tools, checks results, and keeps going until a goal is met. the difference from a chatbot is the loop, not the model.
what is agentic orchestration?
coordinating several agents toward a goal without scripting the steps. the orchestrator assigns work, routes results, and decides when the whole thing is done.
what is ai staff?
software agents filling staff roles rather than acting as tools. the phrase also means human ai teams and ai staffing agencies, which is worth untangling before you shop.
what is an agent swarm?
many simple agents producing useful behaviour through local rules and no central controller. in llm practice the word usually just means several agents with handoffs.
what is an ai agent marketplace?
a catalog where you browse and install prebuilt agents or agent skills. four kinds exist, and only one of them actually solves the problem buyers think it solves.
what is an ai software developer?
two meanings: a human who builds software with models in it, or an agent that writes and ships code. context decides which, and the two are usually conflated.
what is an ai teammate?
an agent positioned as a colleague rather than a tool: it sits in your channels, holds context about the work, and takes assignments instead of waiting for prompts.
what is an example of a multi-agent system?
concrete examples, from traffic lights and warehouse robots to a software team of planner, engineers, and reviewer working one codebase together.
what is an example of ai orchestration?
three worked examples: a support ticket routed and resolved, a document pipeline, and a feature shipped by a planner, two engineers, and a reviewer.
what is orchestration in ai?
the layer that decides what runs, in what order, with what data, and what happens when a step fails. it covers three different things people use the same word for.
what is the 30% rule for ai?
there is no single 30% rule. the phrase covers three different claims: an automation ceiling, a productivity gain, and a hallucination budget. only one of them is useful.
what is the ai workforce?
the ai workforce is the set of software agents a company staffs like headcount: named roles, assigned work, a reporting line, and a bill. here is what that actually looks like.
what is the best multi-agent system?
depends on whether you want a framework to build with or a platform to run. langgraph and crewai lead on frameworks. platforms differ on memory, permissions, and gates.
what is the difference between crewai and agent swarm?
crewai is a framework with roles, tasks, and a process. swarm is a pattern, and also an openai library, where agents hand off to each other with no coordinator.
what is the difference between workflow and agentic orchestration?
a workflow decides the path in advance. agentic orchestration decides it at runtime. one is cheaper and debuggable, the other handles branches nobody enumerated.
what jobs are in danger due to ai?
screen work that produces a document and needs no signature. entry-level rungs are going first, which is a bigger problem than whole occupations disappearing.
what workers is ai replacing?
so far: data entry, basic translation, first-draft copy, tier-one support, and junior document review. mostly tasks rather than people, and mostly at the entry level.
which 5 jobs will survive ai?
no list of five is authoritative. the roles that hold up share three traits: physical presence, legal accountability, or a relationship the work cannot be separated from.
which ai agent platform is best for enterprises?
depends which constraint binds. incumbent suites win on procurement, specialists win on outcome, and build-your-own wins only when the agent is your product.
which is the best agentic ai?
there is no single best. the answer splits four ways by what you are automating: coding, customer operations, enterprise workflow, or a whole team. here is the honest split.
which is the best ai agent?
no agent wins every job. sorted by what you need done: coding, browsing, research, support, and running a team. plus the test that beats every leaderboard.
which is the best ai employee?
depends on the role you are filling. the vendors sell canned personas that work solo. the honest test is a fortnight of real work with the completion rate written down.
who are the big 4 ai agents?
there is no official big 4 of ai agents. the phrase borrows from consulting. here is what searchers usually mean by it and which platforms actually belong in the comparison.
who are the major developers of ai?
openai, anthropic, google deepmind, meta, microsoft, nvidia, mistral, alibaba, and deepseek. sorted by whether they build models, hardware, or both.
who is leading in agentic ai?
three separate races: anthropic and openai lead on capability, microsoft and salesforce on distribution, and the application layer is wide open.
want the product, not the definition?
these pages explain the category. the feature pages explain what aldena does inside it: isolated rooms, agent memory, an org chart that delegates, and approval gates.
what aldena does