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.
Matthew Butler
Systems Development Engineer @ Amazon Web Services
Caio Rodrigues
I'm a full-stack developer focused on building practical and scalable web applications. My main experience is with **React, TypeScript, and modern frontend architectures**, where I prioritize clean code, component reusability, and maintainable project structures.
I have strong experience working with **dynamic forms, state management (Redux / React Hook Form), and complex data-driven interfaces**. I enjoy solving real-world problems by turning ideas into reliable software that companies can actually use in their daily operations.
Beyond coding, I care about **software quality and architecture**, following best practices for componentization, code organization, and performance optimization.
I'm also comfortable working across the stack when needed, integrating APIs, handling business logic, and helping transform prototypes into production-ready systems.
My goal is always to deliver solutions that are **simple, efficient, and genuinely useful for the people using them.**
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.
Taufan
I’m a product-focused engineer and tech leader who builds scalable systems and turns ideas into production-ready platforms.
Over the past years, I’ve worked across startups and fast-moving teams, leading backend architecture, improving system reliability, and shipping products used by thousands of users. My strength is not just writing code — but connecting product vision, technical execution, and business impact.
Nam Tran
10 years as fullstack developer
BurnHavoc
Been around fixing other peoples code for 20 years.
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.
zipking
I am a technologist and product builder dedicated to creating high-impact solutions at the intersection of AI and specialized markets. Currently, I am focused on PropScan (EstateGuard), an AI-driven SaaS platform tailored for the Japanese real estate industry, and exploring the potential of Archify.
As an INFJ-T, I approach development with a "systems-thinking" mindset—balancing technical precision with a deep understanding of user needs. I particularly enjoy the challenge of architecting Vertical AI SaaS and optimizing Small Language Models (SLMs) to solve specific, real-world business problems. Whether I'm in a CTO-level leadership role or hands-on with the code, I thrive on building tools that turn complex data into actionable value.
legrab
I'll fill this later
Kingsley Omage
Fullstack software engineer passionate about AI Agents, blockchain, LLMs.
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