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March 11, 2026
·
Berlin
telli's internal agents infrastructure
Learn how internal AI agents provide company-wide access for debugging, product information, bug research, and infrastructure monitoring, inspired by a successful external model.
Overview
How we provide access to the best coding/debugging agent’s to everyone in the company, for :
- debugging call issues
- finding information about the product
- researching bugs
- monitoring infra
(inspired by https://engineering.ramp.com/post/why-we-built-our-background-agent)
Links
Ramp Builders mobile application utilizes bundled ES modules, CSS, metadata.
Tech stack
- PythonPython: The high-level, general-purpose language built for readability, powering everything from web backends to advanced machine learning models.Python is the high-level, general-purpose language prioritizing clear, readable syntax (via significant indentation), ensuring rapid development for any team . Its ecosystem is massive: use it for robust web development with frameworks like Django and Flask, or leverage its power in data science with libraries such as Pandas and NumPy . The Python Package Index (PyPI) provides thousands of community-contributed modules, offering immediate solutions for tasks from network programming to GUI creation . The language is actively maintained by the Python Software Foundation (PSF), with the stable release currently at Python 3.14.0 (as of November 2025) .
- OpenCodePAn open-source framework for large-scale code pre-training and evaluation using curated multi-language datasets.OpenCodeP streamlines the development of code-centric LLMs by providing a unified pipeline for data cleaning, tokenization, and distributed training. It leverages the 1.2TB Stack dataset and specialized benchmarks like HumanEval to ensure high-fidelity performance across 80+ programming languages. The toolkit includes optimized scripts for Megatron-LM and DeepSpeed, enabling developers to scale models from 1B to 33B parameters with verifiable efficiency.
- ModalModal is the unified cloud platform for data and AI, providing elastic, serverless infrastructure to instantly run and deploy any Python code, from zero to thousands of GPUs.Modal delivers high-performance, developer-focused cloud infrastructure for data and AI workloads (LLM fine-tuning, Generative AI inference, computational biotech). The platform is built from the ground up: it features a custom file system, container runtime, and orchestration engine, rejecting standard solutions like Docker and Kubernetes to achieve near-instant boot times. This architecture enables elastic GPU scaling, letting you scale from zero to thousands of CPUs or GPUs in seconds. Pricing is strictly usage-based, ensuring you only pay for the compute time your code is actively running, eliminating fixed cluster costs and capacity planning headaches.
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