Vibes to Production
Vibe-coding is great for validating ideas, but what happens next?
Good Vibes
Your prototype can handle the basics, and you had fun building it.
You’ve vibe-coded your way to securing letters of intent from customers, your product works, and you’ve got interest from investors.
But now you need to get your masterpiece into production.
Bad Vibes
It’s been all over the news: data leaks, hacking, and performance issues.
The LLMs used for vibe coding are trained on public code on sites like GitHub, the vast majority of which is written by university students and coding camp participants, not professional engineers.
The result is obvious: Code that is full of bugs.
Production
Our team of expert engineers will review your code, run static and dynamic analysis tests (including penetration tests) against it and present a report on findings.
We’ll then fix the issues in order of priority, help you to deploy it on either a cloud provider of your choice or our zero-carbon infrastructure, and help you hire and train a team to maintain it.
Our Expertise
Each member of our data team is highly experienced and has built real-world products from the ground up. Each of our engineering squads is led by an engineer with more than a decade of experience.
Our backgrounds span finance, telecoms, and hosting at Fortune 500 companies, start-ups, and scale-ups.
We have spent our careers building software from idea to production, creating entire platforms like Tracr, Lambdanetix, Lounge, and Gameye.
We have responded in real-time to hacking attempts, hit scaling walls and climbed them, and recovered data from servers after fires.
These are all real issues that you will likely face at some point, and when you do, having a prepared battle plan and assistance from someone who’s been through it before will save you a lot of time, money, and pain.
LLMs are great for getting things going, but they don't know the difference between good and bad code.
Our Process
Compliance
As you enter production, there are data security standards and regulations that you need to be compliant with when it comes to storing Personally Identifiable Information (PII) and other user data. Depending on your location, industry, and the type of data, these might include GDPR, ISO27001, SOC2, PCI-DSS, HIPAA, DSP, and many more.
We ensure you have suitable policies in place and enacted to comply with the self-certification requirements.
Security
As AIs/LLMs like ChatGPT, Claude, Loveable, Perplexity, Cohere, etc. cannot tell the difference between secure code and insecure code (latest independent analysis has them scoring around 50-60% in code security tests), we set up code security pipelines (including Linting, Static Analysis Security Testing aka SAST, and Dynamic Analysis Security Testing aka DAST) that run everytime you make a change to your code, helping to ensure that you’re not introducing any known vulnerabilities.
We then create a report on our findings and help fix any existing vulnerabilities.
Performance
Similar to code security, AIs struggle to write performant code, as the vast majority of their training data comes from student projects and beginner tutorials. This leads to inefficient code that is copied verbatim, rather than using properly optimised libraries that have had many software engineers improving them over the years.
We identify the performance bottlenecks and help resolve them.
Deployment
The biggest LLM-related security breaches that have afflicted companies (like Tea, Deepseek, OmniGPT, OpenAI, etc.) have been due to misconfiguration of databases and basic cloud security policies.
Our team utilise their experience in DevOps and Platform Engineering to ensure that your deployments are compliant with the Best Current Operational Practices (BCOPs), either on your cloud or, with our partners at Leaf.Cloud, on our carbon-neutral managed hosting services.