Replit
performance
High Token Usage from AI Agent on Replit
Your AI agent consumes excessive tokens causing high API costs. Each request uses thousands of tokens unnecessarily.
Verbose prompts, large context windows, and inefficient tool use waste tokens.
Common Causes
- Entire codebase in context instead of relevant files
- Verbose system prompt with unnecessary instructions
- Including all previous conversation history
- Tool responses not summarized/truncated
- Multiple tool calls when one would suffice
How to Fix It
Limit context to relevant code only (use file selectors). Summarize system prompt to essential instructions only. Keep conversation history to last N messages. Truncate tool responses to relevant portions. Cache frequently used context. Implement tool result filtering to return only needed data.
Real developers can help you.
Meïr Ankri
Full-stack developer specializing in React / Next.js / Node.js with 6+ years of experience. I've worked across various sectors including automotive (Reezocar/Société Générale), healthcare (Medical Link SaaS), and e-commerce (Glasman). I build web apps end-to-end, from architecture to production, with a focus on scalability, performance, and code quality. I also mentor junior developers and contribute to technical decisions and code reviews.
Rudra Bhikadiya
I build and fix web apps across Next.js, Node.js, and DBs.
Comfortable jumping into messy code, broken APIs, and mysterious bugs.
If your project works in theory but not in reality, I help close that gap.
Kingsley Omage
Fullstack software engineer passionate about AI Agents, blockchain, LLMs.
Prakash Prajapati
I’m a Senior Python Developer specializing in building secure, scalable, and highly available systems. I work primarily with Python, Django, FastAPI, Docker, PostgreSQL, and modern AI tooling such as PydanticAI, focusing on clean architecture, strong design principles, and reliable DevOps practices. I enjoy solving complex engineering problems and designing systems that are maintainable, resilient, and built to scale.
Franck Plazanet
I am a Strategic Engineering Leader with over 8 years of experience building high-availability enterprise systems and scaling high-performing technical teams. My focus is on bridging the gap between complex technology and business growth.
Core Expertise:
🚀 Leadership: Managing and coaching teams of 15+ engineers, fostering a culture of accountability and continuous improvement.
🏗️ Architecture: Enterprise Core Systems, Multi-system Integration (ERP/API/ETL), and Core Database Structure.
☁️ Cloud & Scale: AWS Expert; architected systems handling 10B+ monthly requests and managing 100k+ SKUs.
📈 Business Impact: Aligning tech strategy with P&L goals to drive $70k+ in monthly recurring revenue.
I thrive on "out-of-the-box" thinking to solve complex technical bottlenecks and am always looking for ways to use automation to improve business productivity.
Anthony Akpan
Developer with 8 years of experience building softwares fro startups
Matthew Butler
Systems Development Engineer @ Amazon Web Services
Stanislav Prigodich
15+ years building iOS and web apps at startups and enterprise companies. I want to use that experience to help builders ship real products - when something breaks, I'm here to fix it.
Alvin Voo
I’ve watched the tech landscape evolve over the last decade—from the structured days of Java Server Pages to the current "wild west" of Agentic-driven development. While AI can "vibe" a frontend into existence, I specialize in the architecture that keeps it from collapsing.
My expertise lies in the critical backend infrastructure: the parts that must be fast, secure, and scalable. I thrive on high-pressure environments, such as when I had only three weeks to architect and launch an Ethereum redemption system with minimal prior crypto knowledge, turning it into a major revenue stream.
What I bring to your project:
Forensic Debugging: I don't just "patch" bugs; I use tools like Datadog and Explain Analyzers to map out bottlenecks and resolve root causes—like significantly reducing memory usage by optimizing complex DB joins.
Full-Stack Context: Deep experience in Node.js and React, ensuring backends play perfectly with mobile and web teams.
Sanity in the Age of AI: I bridge the gap between "best practices" and modern speed, ensuring your project isn't just built fast, but built to last.
Mehdi Ben Haddou
- Founder of Chessigma (1M+ users) & many small projects
- ex Founding Engineer @Uplane (YC F25)
- ex Software Engineer @Amazon and @Booking.com
You don't need to be technical. Just describe what's wrong and a verified developer will handle the rest.
Get HelpFrequently Asked Questions
How do I estimate token cost?
OpenAI: ~4 tokens per word. Monitor API usage dashboard
Should I include full repo context?
No. Use file search first to identify relevant files, then include only those