Build a Basic AI Agent from Scratch: Tools
The article discusses the development of a basic AI agent and the importance of tools in enhancing its functionality. It explains how tools allow the agent to perform actions in its environment, such as executing commands or reading files. The article also outlines several essential tools that can be implemented to improve the agent's capabilities.
- ▪The basic AI agent can only interact through user input and internal knowledge without tools.
- ▪Tools are programs or functions that enable the AI agent to take actions autonomously.
- ▪Modern large language models have native tool calling features that improve reliability and minimize errors.
Hacker News (Newest) files mainly under programming. We currently carry 5,306 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Medium |
| Canonical URL | https://medium.com/@rogi23696/build-a-basic-ai-agent-from-scratch-tools-4fcd71ea33be |
| Publication time | Wed, 03 Jun 2026 13:31:26 +0000 |
| Retrieval time | 2026-06-03T13:42:08.547Z |
| Last seen | 2026-06-03T13:42:08.547Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 6hMQsvfQVcRf |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Build A Basic AI Agent From Scratch: ToolsRoger Oriol9 min read·1 day ago--ListenShareIn the previous part of the Build A Basic AI Agent From Scratch series, we built the most basic AI agent harness possible. It was just a connection to a model, a way to take user input, a store of context of the conversation and a loop that kept the agent running.Of course, this agent is not very useful. It can only interact by taking your input and answering you based on its internal knowledge. If we want our agent to be more useful and do work in behalf of us, we have to give it a way to give it some way to take actions in its environment. In this case, the computer it’s running on.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Medium.
Discussion
0 commentsMore from Medium
