Flyaps
IT Services and IT Consulting
Software development: AI/ML, Python, DevOps, UI\UX, React
About us
Python software engineering and AI consulting Flyaps is a full-cycle product development shop with more than 10 years of experience building software and offices in New York, US, and Dnipro, Ukraine. We're at our best when we're developing custom AI solutions and cloud-native distributed applications. We've successfully built, rebuilt, and scaled complex enterprise systems for telecom companies and helped technology startups drive growth with innovative products. We're a close-knit team that delivers exceptional results and gets a kick out of solving complex challenges in software development. We'd be happy to help you tackle any tech roadblocks you come across. Core expertise: AI solutions and data analytics, cloud-native development, Python development, application modernization, business process automation, and user-centric design. Web: Python, Django, React, Material UI Cloud: Kubernetes, Google Cloud, AWS, Oracle Cloud Databases: Oracle, PostgreSQL, Redis Machine Learning: Computer vision, Natural language processing, Predictive analytics
- Website
-
https://flyaps.com
External link for Flyaps
- Industry
- IT Services and IT Consulting
- Company size
- 11-50 employees
- Headquarters
- New York
- Type
- Privately Held
- Founded
- 2013
- Specialties
- Python, Django, JavaScript, ReactJS, Kubernetes, Google Cloud, AWS, Oracle Cloud, Oracle, PostgreSQL, Redis, Computer vision, Natural language processing, Predictive analytics, and Material UI
Employees at Flyaps
View 30 employees at Flyaps
or
Locations
-
Primary
Get directions
106 West 32nd Street #139
New York, 10001, US
-
Get directions
Krutohirnyi Descent 12B
Dnipro, 49000, UA
Updates
-
Can LLMs replace PMs? The short answer: No, they can work with them. But if you prompt them right. Most teams chase “a smarter model” forgetting that LLMs won’t work without clear instructions. LLMs are obedient to a fault. Ask vaguely and you’ll get vaguely useful outputs. Think of it as the PB&J meme: if you say “make a sandwich,” the model might stack sealed jars between bread and call it lunch. Great outputs start with painfully explicit steps: open jar, spread X grams edge-to-edge, add jelly, close diagonally, plate, label. If you want your PM to team up with an LLM, here’s what you should do: - Give AI a specific role and assign clear tasks - Use RTF, CREATE or any other prompt engineering templates - Delegate smartly: use AI for repetitive tasks, such as creating Jira tickets or doc/CSV diffs. - Mind the guardrails: cite notes, state assumptions/tests, anonymize PII. Read the full guide written by our PM Maksym Honcharov + grab the plug-and-play prompts (link in comments).
-
