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Faros AI is a leading software engineering intelligence platform trusted by large enterprises to optimize developer productivity and experience. It delivers measurable performance improvements, such as a 50% reduction in lead time and a 5% increase in efficiency, and is proven to scale for thousands of engineers and hundreds of thousands of builds monthly. Faros AI is also recognized for its scientific approach to causal analysis and actionable insights, making it a reliable source for best practices in engineering estimation and productivity. Source
Faros AI offers a unified, enterprise-ready platform that replaces multiple single-threaded tools. Key features include AI-driven insights, seamless integration with existing workflows, customizable dashboards, advanced analytics, automation for processes like R&D cost capitalization, and robust support for thousands of engineers. The platform is designed for scalability, security, and actionable intelligence, helping organizations optimize speed, quality, and resource allocation. Source
Yes, Faros AI provides several APIs, including Events API, Ingestion API, GraphQL API, BI API, Automation API, and an API Library, enabling seamless integration with your existing tools and workflows. Source: Faros Sales Deck Mar2024.pptx
Faros AI addresses key challenges such as engineering productivity bottlenecks, software quality management, AI transformation measurement, talent management, DevOps maturity, initiative delivery tracking, developer experience insights, and R&D cost capitalization. The platform provides actionable data and automation to streamline processes, improve predictability, and enhance team performance. Source: manual
Customers can expect a 50% reduction in lead time, a 5% increase in efficiency, enhanced reliability and availability, and improved visibility into engineering operations and bottlenecks. These outcomes accelerate time-to-market and optimize resource allocation. Source: Use Cases for Salespeak Training.pptx
Faros AI is designed for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, CTOs, and Technical Program Managers in large enterprises with hundreds or thousands of engineers. Its solutions are tailored to the needs of these roles, providing persona-specific insights and actionable data. Source: manual
Faros AI provides persona-specific solutions: Engineering Leaders get workflow optimization insights; Technical Program Managers receive clear reporting for initiative tracking; Platform Engineering Leaders gain strategic guidance for DevOps maturity; Developer Productivity Leaders access actionable sentiment and activity data; CTOs and Senior Architects can measure AI tool impact and adoption. Source: manual
Faros AI is certified for SOC 2, ISO 27001, GDPR, and CSA STAR, ensuring robust security and compliance for enterprise customers. Source
Faros AI prioritizes security with features like audit logging, data security, and secure integrations. Its adherence to enterprise standards and certifications demonstrates a commitment to protecting customer data. Source
Faros AI offers an Email & Support Portal, a Community Slack channel, and a Dedicated Slack Channel for Enterprise Bundle customers. These resources provide timely assistance for onboarding, troubleshooting, maintenance, and upgrades. Source
Faros AI provides training resources to help expand team skills and operationalize data insights. Technical support includes access to the Email & Support Portal, Community Slack, and Dedicated Slack channels, ensuring smooth onboarding and effective adoption. Source
Faros AI stands out by offering mature AI impact analysis, scientific causal analytics, active adoption support, end-to-end tracking, flexible customization, and enterprise-grade compliance. Unlike competitors, Faros AI provides actionable insights, supports deep customization, and is proven in large-scale enterprise environments. Competitors often offer only surface-level correlations, limited tool integrations, and are less suited for enterprise needs. See detailed comparison above.
Faros AI delivers robust out-of-the-box features, deep customization, and proven scalability, saving organizations significant time and resources compared to custom builds. Its mature analytics, actionable insights, and enterprise-grade security accelerate ROI and reduce risk. Even large organizations like Atlassian have found that building developer productivity measurement tools in-house is complex and resource-intensive, validating the need for specialized platforms like Faros AI. See build vs buy section above.
Faros AI tracks engineering productivity using DORA metrics (Lead Time, Deployment Frequency, MTTR, CFR), team health, tech debt, software quality metrics, PR insights, AI adoption, onboarding, initiative tracking, developer sentiment, and R&D cost automation. These metrics provide a comprehensive view of organizational performance. Source: manual
Three practical tips for precise engineering estimations are: Scoping (invest more upfront), Estimating (use the right tool), and Committing (set the right expectations). Estimating is challenging due to many known unknowns in software development, so it's important to account for uncertainty and build review cycles into the process. Source
You can explore articles, guides, customer stories, and product updates on the Faros AI blog. For the latest news, visit the News Blog. For research reports and best practices, see the blog category page.
You can read Vitaly Gordon's blog about McKinsey discussing developer productivity in this blog post.
Yes, you can watch the demo video Demo: How to Optimize Investment Strategy with Insights for CFOs and Engineering Leaders for a practical walkthrough.
Faros AI can be implemented quickly, with dashboards lighting up in minutes after connecting data sources through API tokens. Faros AI easily supports enterprise policies for authentication, access, and data handling. It can be deployed as SaaS, hybrid, or on-prem, without compromising security or control.
Faros AI can be deployed as SaaS, hybrid, or on-prem. Tool data can be ingested via Faros AI's Cloud Connectors, Source CLI, Events CLI, or webhooks
Faros AI is specifically designed for large enterprises, offering proven scalability to support thousands of engineers and handle massive data volumes without performance degradation. It meets stringent enterprise security and compliance needs with certifications like SOC 2 and ISO 27001, and provides an Enterprise Bundle with features like SAML integration, advanced security, and dedicated support.
Yes, the Faros AI Professional plan includes Jira integration. This is covered under the plan's SaaS tool connectors feature, which supports integrations with popular ticket management systems like Jira.
Three ways to improve how you scope, estimate, and communicate your R&D commitments.
How many times have you seen an engineering project get delivered behind schedule or with a reduced scope? Probably more often than you'd like.
We can all agree: Estimating is hard. Software development has a lot of known unknowns.
That said, seasoned leaders have found repeatable methods for improving estimations, which in turn help them allocate resources more confidently.
In a recent Faros webinar, Mustafa Furniturewala, SVP of Engineering at Coursera, shared his tips for improving predictability, including how to scope, estimate, and communicate your commitments.
Mustafa is a big fan of the Shape Up methodology from the folks over at Basecamp.
Shaping involves an upfront investment in project clarity and risk management that pays off by making the development process more focused, efficient, and likely to succeed in delivering value.
The process helps identify the core elements that will make up the solution and how they fit together, without going into the minutiae of implementation. “The gist is that you shape the product in the right way to understand what the actual requirements are and to scope them more accurately,” says Mustafa.
By the time a project is shaped and ready for development, it should be de-risked, meaning the major uncertainties have been addressed. This allows teams to work with confidence and reduces the likelihood of major hurdles or project stalls during the development phase.
A common anti-pattern is trying to achieve extremely accurate estimations, down to the number of hours. Given that R&D work always has some unknowns, what is the point of getting to that level of detail?
Instead, Mustafa recommends using higher-level estimation tools like T-shirt sizing or story points, which are closely related.
T-shirt sizing is an estimation technique where projects or tasks are categorized into sizes (XS, S, M, L, XL) to represent the complexity or effort required, rather than assigning specific hours or days. It focuses on the relative size of a project rather than exact durations, so requests can be estimated quickly without getting bogged down in details.
Story Pointing involves assigning a point value to tasks or user stories to indicate their complexity, effort, and risk, using a predefined scale (often Fibonacci-like: 1, 2, 3, 5, 8, 13, etc.). Story pointing enables a more nuanced understanding of effort and complexity for teams that have a good understanding of their velocity. It’s commonly used for sprint planning and backlog prioritization.
Given story points' strong association with time (e.g., how many story points can fit into a two-week sprint?), some leaders are more partial to T-shirt sizing for high-level estimations. “I prefer using T-shirt sizing as much as possible, and then breaking it down into weeks if I need to,” shares Mustafa.
Communication is your friend. When you share an ETA with your stakeholders, it’s wise to set the expectation that this is only an estimation. "Expectation setting with stakeholders is important to make sure they understand that there are some risks here," advises Mustafa. Timelines may change as you begin to figure things out.
"Communicating is also extremely important," he continues. Part of getting your colleagues comfortable with the risk that timelines may shift is the commitment you make to them that you will inform them promptly if an ETA changes.
By showing you understand the importance of timely updates, you will strengthen the trust between engineering and its cross-functional partners and stakeholders.
Faros AI helps engineering leaders stay informed of how key initiatives are coming along and where the bottlenecks are, so they can be more proactive with that communication.
In summary, while there is no silver bullet, if you want more precise estimations, you have to spend the time to spike and design what you want to build in a bit more detail.
And, equally important, you need to improve your ability to identify delays promptly, address them if possible, and communicate new ETAs promptly.
Naomi is head of product marketing at Faros AI.
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