How I use agents for my personal projects

May 26, 2026 · 12:56 PM UTC ·3 min read · 0 reactions · 0 comments · 25 views

TL;DR · WeSearch summary

The article discusses the author's experience using AI agents for personal projects. It highlights the high costs associated with these agents and offers insights on how to manage token usage effectively. The author shares specific tools and strategies to optimize productivity while minimizing expenses.

Key facts

▪Agents can be very expensive, with costs reaching up to $150-170 a month depending on usage.
▪The author uses two agents and one LLM, focusing on specific tasks like code reviews and generating tests.
▪Explicitly guiding agents with detailed prompts helps save tokens and reduces unnecessary costs.

How this story was covered

3 outlets in our directory ran this story, first to last over 35 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.

Centre · 2

▪ How do people actually use AI for editorial work? — r/OpenAI
▪ How AI coding agents actually use your technology — Microsoft Dev Blogs

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DEV.to (Top) files mainly under programming. We currently carry 4,924 of its stories.

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Record

Original publisher	DEV.to (Top)
Canonical URL	https://dev.to/crusty0gphr/how-i-use-agents-for-my-personal-projects-1j5b
Publication time	Tue, 26 May 2026 12:56:29 +0000
Retrieval time	2026-05-26T13:07:49.469Z
Last seen	2026-05-26T13:07:49.469Z
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	4M-KwIc6U3SZ · 3 stories
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

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Unknown

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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.

Open original publisher → Source rights JSON → Machine-readable provenance → Rights framework → WESEARCH-STORY-PROVENANCE-V1

Opening excerpt (first ~120 words) tap to expand

try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 50319) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Harutyun Mardirossian Posted on May 26 How I use agents for my personal projects #ai #agents #programming #productivity Agents are expensive, like awfully expensive. For example, Claude can charge up to $25 per million tokens, almost the same, but a little bit cheaper, for Codex from OpenAI. So in rough calculations, depending on usage, you can spend up to $150-170 a month (if you check Reddit, people proudly burn $2k-4k a month, this is insanely expensive).

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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).

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