The project is still in its early stages but people familiar with the matter say it may take months before it is ready.

Engineers at OpenAI began exploring the idea after repeated service disruptions on GitHub in recent months disrupted their work. Those outages forced internal teams to reassess how much they rely on external platforms.

From what has been reported, OpenAI has discussed offering the repository as a paid service to its existing customers. That would place it in direct competition with GitHub, which is owned by Microsoft.

Neither OpenAI nor Microsoft has publicly confirmed the plan. The companies did not respond to requests for comment at the time of publication.

If OpenAI moves forward, the decision would test its relationship with Microsoft. The software giant is one of OpenAI’s biggest backers and also controls GitHub, which serves more than 100 million developers worldwide. A competing product from OpenAI would be a rare overlap in their commercial interests.

In February 2026, OpenAI closed a $110 billion funding round that valued the company at $840 billion. Investors in that raise included Amazon, Nvidia and SoftBank.

The deal stands among the largest private capital raises to date and places OpenAI ahead of competitors such as Anthropic and Inflection in valuation terms.

For now, the proposed platform is still under development, with OpenAI still weighing whether to build more of its own infrastructure rather than depend on tools owned by partners.

Coding has become the most commercially valuable use of advanced models. Whoever controls the developer workflow stands to win enterprise contracts. Right now, OpenAI is focusing on that aspect.

For months, developers have been shifting towards tools that can handle long, messy jobs without constant supervision. These systems can break work into parts, run tasks at the same time and keep going for hours or days. 

OpenAI’s earlier Codex releases worked, but they were awkward. Many users went elsewhere.

The new app is meant to change that. It gives developers a single desktop space to oversee several coding agents at once, switch between projects without losing context and review changes before they touch the main codebase. 

Each agent works in isolation, which reduces the risk of conflicts. The company is also pushing Codex beyond writing lines of code.

The app can now be used to gather information, run workflows, generate documents and even deploy software, all from the same interface. 

Developers can define specific “skills” that tell Codex how to interact with tools they already use, from design software to cloud hosting platforms. Once set up, those skills can be reused across teams.

This approach shows how modern development actually works. Software has gone beyond typing code. It involves design, testing, deployment, bug tracking and documentation. OpenAI is trying to sit at the centre of that entire process.

There is also a commercial angle. OpenAI says Codex will, for a limited time, be included for users on its free and low-cost plans, while usage limits are being raised for paid customers.

This could pull more developers into its ecosystem and slow the focus on competitors.

Anthropic’s Claude Code has built a strong following and, by the company’s own account, reached an annualised revenue run rate of $1 billion within six months of launch.

That kind of figure gets attention and OpenAI’s response has been to tighten its tooling and lean on the strength of its latest coding model.

Speaking to reporters, OpenAI chief executive Sam Altman argued that the underlying technology now needs a better wrapper. “If you really want to do sophisticated work on something complex, 5.2 is the strongest model by far,” he said.

“However, it’s been harder to use, so taking that level of model capability and putting it in a more flexible interface, we think is going to matter quite a bit.”

Tests that measure how well systems handle command-line tasks or fix real software bugs show little separation between the leading tools. Usually, developers care less about marginal scores and more about whether a tool fits their workflow and saves time.

That is where OpenAI is aiming. The Codex app allows background automations to run on a schedule, flagging results for review later. Users can also choose how the agent communicates, from blunt and task-focused to more conversational.

These may sound like small details, but they determine whether people stick with a tool day after day.

Altman noted the advantage as speed. “You can use this from a clean sheet of paper, brand new, to make a really quite sophisticated piece of software in a few hours,” he said. “As fast as I can type in new ideas, that is the limit of what can get built.”

Not everyone believes these tools are ready to replace human developers, and OpenAI does not claim they are. What they do is remove drudge work and compress timelines. In a tight labour market, that alone is valuable.

For now, the OpenAI Codex desktop app is only available on macOS, with a Windows version promised later. The company says usage has already surged since the release of its latest coding model, with more than a million developers using Codex in the past month.

The deal, announced Thursday, aims to sharpen how Andela identifies and deploys engineers who can deliver on AI projects at scale.

“With Woven, Andela is leapfrogging the development of world-class assessments for both AI fluency and engineering fundamentals,” said Barun Singh, Andela’s chief product and technology officer.

The acquisition will enable Andela to meet the high demand for AI-native engineers, professionals who not only experiment with AI but also build, integrate, and scale AI systems. 

Andela describes three critical archetypes for enterprises, including builders, integrators, and scalers. Builders turn business needs into functional AI components. Integrators connect models, data, and tools into autonomous workflows. 

Scalers manage reliability, governance, and risk in deployed AI systems. Woven’s technology will now allow Andela to assess engineers accurately across all three roles, helping companies hire the right talent for each stage of AI adoption.

“To power the AI ecosystem at scale, the world needs AI-native, enterprise-ready engineering talent en masse. Andela plus Woven equals the best technical assessment engine in the world to ensure AI fluency and real-world job success,” said Carrol Chang, Andela’s CEO.

As part of the integration, Woven’s founder and CEO, Wes Winham Winler, will join Andela to lead next-generation assessments focused on AI-assisted software development and AI system creation. 

The company will also gain access to Woven’s library of engineering scenarios, AI-driven scoring systems, and the team’s domain expertise to accelerate its roadmap.

Andela’s platform already connects more than 150,000 technology professionals worldwide. With Woven’s capabilities built on top of Andela’s previously acquired Qualified platform, the company now has a unified system for scalable, high-accuracy engineering assessments.

This is the third major Nigerian startup acquisition this month. Earlier in January, Flutterwave bought Mono, an open banking startup, while Paystack acquired Ladder Microfinance Bank, revealing a trend of consolidation and expansion in Nigeria’s tech sector.

Andela wants to become the global hub for AI-native engineering talent, combining deep assessment strength with a large, verified talent network to ensure engineers are both skilled and ready for real-world AI challenges.

Selected developers will receive a $500 voucher to build with the X API and gain early access to a revamped Developer Console, which aims for a more flexible and transparent experience. “We are expanding a closed beta to both new & power users who want to ship amazing apps on X,” the platform’s developer account posted.

The new model breaks away from X’s previous flat-rate structure by introducing granular pricing for various request types, including reading posts, sending direct messages, accessing trends, and pulling bookmarks. 

A built-in calculator now allows developers to estimate costs based on projected usage, a move the company says will help teams manage their spending with greater precision.

Unlike the old tiered system, which offered Basic ($200 per month), Pro ($5,000 per month), and Enterprise ($42,000 per month) plans, the pay-per-use framework is designed for a wider spectrum of developers, from startups to large-scale enterprises.

Many in the community had previously criticised the old model for being unaffordable and inflexible, particularly after X ended free API access in 2023.

That decision led to the shutdown of several popular third-party apps such as Tweetbot and Twitterrific, further affecting relations between X and its developer base. In a bid to ease some of that tension, the company later introduced top-up packs for developers who exceeded their usage limits.

Now, with this usage-based system, X appears keen to reposition itself as a platform that supports innovation rather than restricts it. Developers selected for the beta will be among the first to test the updated tools and pricing structure before a wider rollout.

Analysts say the pay-per-use API beta could help revive developer engagement on the platform, allowing X to compete more effectively with companies like Reddit, Discord, and Mastodon, all of which offer comparatively accessible API frameworks.

The company has built this model as a tool for both conversation and solving real enterprise problems in sectors like software engineering, financial services, and healthcare.

From day one, GPT-5 will replace its predecessors across ChatGPT platforms, and it’s being offered with expanded access tiers, including free usage, a $20/month Plus subscription, and a $200/month Pro tier. 

Developers also now have access through the OpenAI API, with three variants: GPT-5, GPT-5-mini, and GPT-5-nano. These versions differ in how long they spend “thinking” about problems, with pricing ranging from $1.25 to $10 per million tokens.

While consumer interest in AI remains high, enterprise adoption has been slower. OpenAI is hoping GPT-5 can tip the scale. The model delivers what CEO Sam Altman called “software on demand,” capable of building fully functional apps from natural language prompts. 

“GPT-5 is really the first time that I think one of our mainline models has felt like you can ask a legitimate expert, a PhD-level expert, anything,” Altman said during a press conference.

Behind the launch, OpenAI has struggled with the sheer technical demands of scaling up its models. The company has faced hardware failures during training, hit limits in the availability of new high-quality training data, and spent months waiting for results from high-cost training runs. 

At the same time, it has had to justify its skyrocketing costs, including investor expectations built on a potential $500 billion valuation and signing bonuses of up to $100 million for top AI talent.

Back then, when GPT-4 was launched, it passed a simulated bar exam in the top 10%, compared to GPT-3.5’s performance in the bottom 10%. With GPT-5, the upgrades are more subtle but targeted.

Take code generation. On SWE-bench Verified, a real-world benchmark for software engineering tasks, GPT-5 scored 74.9% on first attempts, outperforming Claude Opus 4.1 from Anthropic (74.5%) and Gemini 2.5 Pro from Google DeepMind (59.6%). In healthcare, its error rate on HealthBench Hard Hallucinations is 1.6%, far below GPT-4o’s 12.9%.

In science, GPT-5 Pro achieved 89.4% accuracy on PhD-level science queries, slightly ahead of rivals from xAI and Anthropic. But it lags in other areas, including real-time web navigation tasks. On the Tau-bench airline site navigation test, GPT-5 scored 63.5%, slightly behind OpenAI’s earlier o3 model (64.8%).

Despite these nuanced results, OpenAI insists the model is “safer, smarter, and more useful.” Alex Beutel, the company’s lead on safety research, said GPT-5’s reduced deception rates are essential for building trust. 

“It’s more transparent and honest in ways users can trust,” he said, adding that GPT-5 also more reliably filters out harmful queries while reducing false positives, unnecessary content rejections.

From a usability standpoint, GPT-5 also comes with new personalisation features. Users can now select from four built-in personalities, Cynic, Robot, Listener, and Nerd, which adjust the tone and structure of responses. Unlike earlier models, users no longer have to manually tweak settings to get different types of output.

Internally, OpenAI believes GPT-5 represents a shift in how people will use AI, not just to answer questions, but to act more like agents or assistants. 

That includes handling schedules, creating research briefs, analysing financial documents, and building apps from scratch. “This idea of software on demand is going to be one of the defining features of the GPT-5 era,” Altman said.

But while the ambition is high, there’s still caution among experts. Some reviewers told Reuters they weren’t convinced GPT-5 is a major leap over GPT-4. Others, like Noah Smith, raised concerns about the financial sustainability of current AI development. 

“Business spending on AI has been pretty weak, while consumer spending has been fairly robust because people love to chat with ChatGPT,” he said. “But the consumer spending on AI just isn’t going to be nearly enough to justify all the money that is being spent on AI data centres.”

Altman himself admitted GPT-5 still has limitations, especially around independent learning. It cannot, on its own, acquire new knowledge or skills without user input. And while test-time compute (a method of giving the model more thinking power when needed) helps in solving complex problems, it’s not a substitute for self-directed learning.

Still, the company believes in its innovation. With over 700 million weekly ChatGPT users and increasing partnerships with enterprise customers, GPT-5 may help OpenAI bridge the gap between consumer curiosity and business utility.

Through years of dedication, Peter Coates has cultivated a community that thrives on collaboration, shared knowledge, and mutual growth.

In a recent discussion, Peter Coates reflected on the pivotal role mentorship has played in his professional life. “When I began my career, I benefited immensely from mentors who guided me through technical challenges and helped me navigate the industry,” he shared. “Mentorship is not just about transferring knowledge—it’s about opening doors, building confidence, and inspiring others to achieve their potential.”

Peter Coates’s approach to mentorship is deeply personal. He strives to understand the unique challenges faced by each mentee, offering guidance that extends beyond technical skills.

“I’ve mentored people transitioning from non-technical fields into software development, and each journey is different,” he explained. “Sometimes, the biggest impact you can have is simply believing in someone and helping them see what’s possible.”

Creating a Space for Aspiring Developers 

Peter Coates’s mentorship efforts extend beyond one-on-one interactions. Through his church outreach programs and involvement in local tech communities, he has created platforms for aspiring developers to learn, connect, and grow. These initiatives have helped young programmers gain hands-on experience, develop critical skills, and build networks that are crucial for career advancement.

“One of the key barriers to entering tech is the lack of access to opportunities,” he noted. “By organizing coding workshops and hackathons, we’re not just teaching skills; we’re building confidence and fostering a sense of belonging.” He recounted the story of a mentee who attended one of his workshops and later secured a junior developer role at a well-known company. “Seeing someone succeed because of the opportunities you’ve helped create is incredibly rewarding,” he added.

Tackling Diversity and Inclusion in Tech

Peter Coates is also a strong advocate for diversity and inclusion in the tech industry. He believes that mentorship is a powerful tool for addressing systemic barriers and creating a more equitable landscape. “Diversity in tech isn’t just a moral imperative—it’s a business necessity,” he emphasized. “When we bring in perspectives from different backgrounds, we build better products and solve problems more effectively.”

To this end, he has focused on mentoring underrepresented groups, including women and individuals from minority communities. He recalled a time when a female mentee expressed hesitation about pursuing a career in tech due to gender stereotypes. “We worked together to rebuild her confidence and map out a plan for achieving her goals,” he said. “Today, she’s thriving as a software engineer, and her success is a testament to the power of mentorship.”

Balancing Technical and Soft Skills

When asked about the skills he emphasizes in mentorship, Peter Coates explained that he takes a holistic approach. “Technical skills are important, but they’re only part of the equation,” he remarked. “Soft skills like communication, teamwork, and problem-solving are equally critical for success in the tech industry.”

He shared an example of a mentee who struggled with presenting technical ideas to non-technical stakeholders. “We worked on simplifying his explanations and building his

confidence in public speaking,” Peter Coates recounted. “Now, he’s leading meetings and presenting ideas that drive significant business decisions.”

Mentorship in the Age of Remote Work

The shift to remote work has transformed the way mentorship is conducted, and Peter Coates has embraced this change. “While virtual mentorship presents its own challenges, it also opens up opportunities to connect with people from around the world,” he observed. He now mentors individuals across different countries, using video calls, collaborative tools, and online resources to bridge the gap.

“The key to effective remote mentorship is communication,” he advised. “You need to be proactive in checking in, setting clear goals, and providing feedback.” He also highlighted the importance of creating a sense of community, even in a virtual setting. “It’s about making people feel that they’re part of something bigger than themselves,” he said.

Lessons Learned and the Path Forward

Reflecting on his journey as a mentor, Peter Coates shared some of the lessons he has learned along the way. “The most important thing is to listen,” he said. “Every mentee has their own story, and understanding their unique challenges is the first step in providing meaningful guidance.”

He also emphasized the importance of humility. “Mentorship is a two-way street. I’ve learned as much from my mentees as they’ve learned from me,” he acknowledged. This mutual exchange of knowledge and perspectives has enriched his own career and deepened his commitment to building a thriving developer community.

Looking ahead, Peter Coates is excited about expanding his mentorship efforts. He plans to launch an online platform that connects mentors and mentees, offering resources, workshops, and networking opportunities. “The goal is to scale mentorship in a way that reaches more people while maintaining the personal touch that makes it so impactful,” he explained.

An Invitation to the Tech Community

As the conversation came to a close, Peter Coates called on other professionals to invest in mentorship. “The tech industry is built on collaboration, and mentorship is one of the most powerful ways we can support the next generation of talent,” he stated. He urged companies and individuals to prioritize mentorship as part of their efforts to foster innovation and inclusion.

For Peter Sowoolu-Coates, mentorship is more than a professional responsibility—it’s a way to give back, inspire change, and build a brighter future for the tech industry. Through his work, he has demonstrated that by investing in people, we can create communities that not only thrive but also drive meaningful progress.

This significant occasion marks a major step in the country’s commitment to digital transformation and skill development.

Launched in November, the 3MTT program culminated in a grand graduation ceremony that recognized the accomplishments of the fellows.

Of the initial 784 enrolees, 377 completed the program, gaining expertise in high-demand areas such as Software Development, UI/UX Design, Data Analysis & Visualization, Product Management, Data Science, Animation, AI / Machine Learning, Cybersecurity, and DevOps.

In her opening address, Cecilia Adenusi, the co-founder and the program director HSProjects Technologies, expressed deep gratitude towards the Federal Government for its pivotal support, specifically noting the donation of 20 laptops which significantly enhanced the learning experience for the students.

The ceremony was attended by luminaries from the tech industry, including the Honourable Minister Dr. Bosun Tijani, who has been instrumental in the visionary leadership under President Bola Ahmed Tinubu.

The event also featured insights from esteemed mentors Uloma Cynthia Okenyi and Samuel Aramide, who delivered talks on “continuous learning and internship” and “How to build your CV, Social Media handles, and WhatsApp status to attract clients,” respectively.

Another highlight was a speech by Prof. Vincent, who advised the new graduates on forging successful careers in tech, focusing on entrepreneurship and personal branding.

Prof. Vincent specifically urged the graduates to view their tech careers as businesses, encouraging them to give these ventures distinct names as a source of ongoing motivation.

This program aligns with President Bola Ahmed Tinubu’s broader strategy, overseen by the Federal Ministry of Communications, Innovation, and Digital Economy, to create 2 million digital jobs by 2025. The initiative aims to build a robust pipeline of technical talent, critical for enhancing Nigeria’s digital economy.

As the graduates’ step into future opportunities, they carry not only advanced technical skills but also the collective hopes for a technologically empowered Nigeria.

President Tinubu’s administration has been commended for its role in providing a fertile ground for such transformative educational endeavors, setting a strong foundation for the nation’s digital future.

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I remember having to play an expert role in auditing a particular unicorn startup based out of South Africa. The co-founder of the business was telling me about some of the challenges they were facing within their engineering team. I realised the following:

1. There was no technical product roadmap guiding the software development cycle.
2. There was no clear validation as to why the technologies being deployed to solve users’ problems were the right fit.
3. There was no clear definition of the technical resources for the startup to scale.
4. There was no strategy around resolving technical debt when growth comes.

I diagnosed and detected that the root cause of the challenges this startup faced emanated from the pointer highlighted above. I was able to guide and help resolve these issues.

However, I noticed that these issues are prevalent among many tech  startups within the digital technology space in Africa. Hence, why I have decided to put this article together.

A second story…

A second piece of evidence that proves that this challenge exists among scaling startups is “Evernote”.

Before the company became a unicorn in 2012, it had issues with scaling its software solution as a result of the way it was set up initially.

There were issues with latency, downtimes, and technical debt, meanwhile, the numbers for user growth grew by leaps and bounds, and it was hard to keep up.

Evernote finally shut down in 2015. The cost of not setting up software development properly can be very steep, for any type of startup.

That brings us to two junctures:

1. How do we set up software development properly (when it had not been set up at all)?
2. How do we fix software development properly when it has been wrongly set up?

How do we set up software development properly (when it had not been set up at all)?

The answer to this is by ensuring the following are done:

1. Hire quality software developers and solution architects: There are a lot of decisions engineers make at the nascent stage of a product. These decisions can make or mar the startup in future. It is important to hire properly. Hiring engineers with more experience and more commitment to work will save the startup a lot of engineering costs. If you are a non-technical co-founder, it is advisable to get someone who is very experienced with tech that can advise you while you are mustering up your first team.
2. Keep proper documentation: Keeping proper documentation is another step that is important during the setup stage. A product manager can be hired to take this up. Important documents like user stories, user research, product requirement documents, user flows, etc. are very important documentation the startup needs at the early stages.
3. Forecast growth and position for scale: Having a prognostic and descriptive perspective in software development is crucial. It is important we factor in traffic volumes and data accruement while designing the software architect and developing the same. It is a thing to know how to drive growth, it is another to know how to manage growth. The software team needs to be aware of this and plan for this.

How do we fix software development properly when it has been wrongly set up?

1. Isolate the issues on the flawed platform while working on a new fix: At this point, the best thing is to identify the flaws within the system and map out a new fix. This might mean creating a new test environment or sandbox. The new changes can then be pushed to this new environment and then merged to production after it has been successfully tested. It is important to consult with a DevOps professional or Solutions Architect if the issues are based on the system’s framework.
2. Hire specialists to assess the risks of change: While working on setting up properly, it is important to conduct a risk assessment of the before state and after state of the changes intended. This anticipation of the risks helps in creating pathways that can help avert these risks e.g this could mean creating a backup on the database, firewall protection, etc.
3. Plan for user migration: If the changes required mean a new platform needs to be instituted, a proper migration plan needs to be created.
4. Ensure good customer support is in place: While changes are being made to the system, it is crucial to make sure the user experience is not impacted negatively. There needs to be a strategic plan to use customer support to cover up for the gaps the new implementation might create.

To contextualize it better, here is an expectation of the technical infrastructure needed based on the business stages of the startup.

Infrastructure Readiness Chart Based on Startup Stages:

To further help, I have prepared a worksheet called the “Scalability matrix”. This free resource will help in guiding you on the status and readiness of your startup’s software development process.

Here is a filled sample below:

Feel free to access this free worksheet HERE.

With the above, I believe setting up software development for your startup will no longer be a chore.